├── Input.xlsx ├── Objective.docx ├── Output Data Structure.xlsx ├── README.md ├── StopWords ├── StopWords_Auditor.txt ├── StopWords_Currencies.txt ├── StopWords_DatesandNumbers.txt ├── StopWords_Generic.txt ├── StopWords_GenericLong.txt ├── StopWords_Geographic.txt └── StopWords_Names.txt ├── Text Analysis.docx ├── analysis result ├── analysis_results.csv ├── analysis_results.xlsx ├── average_word_length.csv ├── average_words_per_sentence_results.csv ├── finaltext_analysis_results.xlsx ├── personal_pronouns_count.csv ├── readability_analysis_results.csv ├── results.csv ├── sentiment_analysis_results.csv ├── syllable_count_results.csv ├── textual_analysis_results.xlsx └── word_count_results.csv ├── cleaned_articles ├── bctech2011.txt ├── bctech2012.txt ├── bctech2013.txt ├── bctech2014.txt ├── bctech2015.txt ├── bctech2016.txt ├── bctech2017.txt ├── bctech2018.txt ├── bctech2019.txt ├── bctech2020.txt ├── bctech2021.txt ├── bctech2022.txt ├── bctech2023.txt ├── bctech2024.txt ├── bctech2025.txt ├── bctech2026.txt ├── bctech2027.txt ├── bctech2028.txt ├── bctech2029.txt ├── bctech2030.txt ├── bctech2031.txt ├── bctech2032.txt ├── bctech2033.txt ├── bctech2034.txt ├── bctech2035.txt ├── bctech2036.txt ├── bctech2037.txt ├── bctech2038.txt ├── bctech2039.txt ├── bctech2040.txt ├── bctech2041.txt ├── bctech2042.txt ├── bctech2043.txt ├── bctech2044.txt ├── bctech2045.txt ├── bctech2046.txt ├── bctech2047.txt ├── bctech2048.txt ├── bctech2049.txt ├── bctech2050.txt ├── bctech2051.txt ├── bctech2052.txt ├── bctech2053.txt ├── bctech2054.txt ├── bctech2055.txt ├── bctech2056.txt ├── bctech2057.txt ├── bctech2058.txt ├── bctech2059.txt ├── bctech2060.txt ├── bctech2061.txt ├── bctech2062.txt ├── bctech2063.txt ├── bctech2064.txt ├── bctech2065.txt ├── bctech2066.txt ├── bctech2067.txt ├── bctech2068.txt ├── bctech2069.txt ├── bctech2070.txt ├── bctech2071.txt ├── bctech2072.txt ├── bctech2073.txt ├── bctech2074.txt ├── bctech2075.txt ├── bctech2076.txt ├── bctech2077.txt ├── bctech2078.txt ├── bctech2079.txt ├── bctech2080.txt ├── bctech2081.txt ├── bctech2082.txt ├── bctech2083.txt ├── bctech2084.txt ├── bctech2085.txt ├── bctech2086.txt ├── bctech2087.txt ├── bctech2088.txt ├── bctech2089.txt ├── bctech2090.txt ├── bctech2091.txt ├── bctech2092.txt ├── bctech2093.txt ├── bctech2094.txt ├── bctech2095.txt ├── bctech2096.txt ├── bctech2097.txt ├── bctech2098.txt ├── bctech2099.txt ├── bctech2100.txt ├── bctech2101.txt ├── bctech2102.txt ├── bctech2103.txt ├── bctech2104.txt ├── bctech2105.txt ├── bctech2106.txt ├── bctech2107.txt ├── bctech2108.txt ├── bctech2109.txt ├── bctech2110.txt ├── bctech2111.txt ├── bctech2112.txt ├── bctech2113.txt ├── bctech2114.txt ├── bctech2115.txt ├── bctech2116.txt ├── bctech2117.txt ├── bctech2118.txt ├── bctech2119.txt ├── bctech2120.txt ├── bctech2121.txt ├── bctech2122.txt ├── bctech2123.txt ├── bctech2124.txt ├── bctech2125.txt ├── bctech2126.txt ├── bctech2127.txt ├── bctech2128.txt ├── bctech2129.txt ├── bctech2130.txt ├── bctech2131.txt ├── bctech2132.txt ├── bctech2133.txt ├── bctech2134.txt ├── bctech2135.txt ├── bctech2136.txt ├── bctech2137.txt ├── bctech2138.txt ├── bctech2139.txt ├── bctech2140.txt ├── bctech2141.txt ├── bctech2142.txt ├── bctech2143.txt ├── bctech2144.txt ├── bctech2145.txt ├── bctech2146.txt ├── bctech2147.txt ├── bctech2148.txt ├── bctech2149.txt ├── bctech2150.txt ├── bctech2151.txt ├── bctech2152.txt ├── bctech2153.txt ├── bctech2154.txt ├── bctech2155.txt ├── bctech2156.txt ├── bctech2157.txt └── desktop.ini ├── desktop.ini ├── extracted_articles ├── bctech2011.txt ├── bctech2012.txt ├── bctech2013.txt ├── bctech2014.txt ├── bctech2015.txt ├── bctech2016.txt ├── bctech2017.txt ├── bctech2018.txt ├── bctech2019.txt ├── bctech2020.txt ├── bctech2021.txt ├── bctech2022.txt ├── bctech2023.txt ├── bctech2024.txt ├── bctech2025.txt ├── bctech2026.txt ├── bctech2027.txt ├── bctech2028.txt ├── bctech2029.txt ├── bctech2030.txt ├── bctech2031.txt ├── bctech2032.txt ├── bctech2033.txt ├── bctech2034.txt ├── bctech2035.txt ├── bctech2036.txt ├── bctech2037.txt ├── bctech2038.txt ├── bctech2039.txt ├── bctech2040.txt ├── bctech2041.txt ├── bctech2042.txt ├── bctech2043.txt ├── bctech2044.txt ├── bctech2045.txt ├── bctech2046.txt ├── bctech2047.txt ├── bctech2048.txt ├── bctech2049.txt ├── bctech2050.txt ├── bctech2051.txt ├── bctech2052.txt ├── bctech2053.txt ├── bctech2054.txt ├── bctech2055.txt ├── bctech2056.txt ├── bctech2057.txt ├── bctech2058.txt ├── bctech2059.txt ├── bctech2060.txt ├── bctech2061.txt ├── bctech2062.txt ├── bctech2063.txt ├── bctech2064.txt ├── bctech2065.txt ├── bctech2066.txt ├── bctech2067.txt ├── bctech2068.txt ├── bctech2069.txt ├── bctech2070.txt ├── bctech2071.txt ├── bctech2072.txt ├── bctech2073.txt ├── bctech2074.txt ├── bctech2075.txt ├── bctech2076.txt ├── bctech2077.txt ├── bctech2078.txt ├── bctech2079.txt ├── bctech2080.txt ├── bctech2081.txt ├── bctech2082.txt ├── bctech2083.txt ├── bctech2084.txt ├── bctech2085.txt ├── bctech2086.txt ├── bctech2087.txt ├── bctech2088.txt ├── bctech2089.txt ├── bctech2090.txt ├── bctech2091.txt ├── bctech2092.txt ├── bctech2093.txt ├── bctech2094.txt ├── bctech2095.txt ├── bctech2096.txt ├── bctech2097.txt ├── bctech2098.txt ├── bctech2099.txt ├── bctech2100.txt ├── bctech2101.txt ├── bctech2102.txt ├── bctech2103.txt ├── bctech2104.txt ├── bctech2105.txt ├── bctech2106.txt ├── bctech2107.txt ├── bctech2108.txt ├── bctech2109.txt ├── bctech2110.txt ├── bctech2111.txt ├── bctech2112.txt ├── bctech2113.txt ├── bctech2114.txt ├── bctech2115.txt ├── bctech2116.txt ├── bctech2117.txt ├── bctech2118.txt ├── bctech2119.txt ├── bctech2120.txt ├── bctech2121.txt ├── bctech2122.txt ├── bctech2123.txt ├── bctech2124.txt ├── bctech2125.txt ├── bctech2126.txt ├── bctech2127.txt ├── bctech2128.txt ├── bctech2129.txt ├── bctech2130.txt ├── bctech2131.txt ├── bctech2132.txt ├── bctech2133.txt ├── bctech2134.txt ├── bctech2135.txt ├── bctech2136.txt ├── bctech2137.txt ├── bctech2138.txt ├── bctech2139.txt ├── bctech2140.txt ├── bctech2141.txt ├── bctech2142.txt ├── bctech2143.txt ├── bctech2144.txt ├── bctech2145.txt ├── bctech2146.txt ├── bctech2147.txt ├── bctech2148.txt ├── bctech2149.txt ├── bctech2150.txt ├── bctech2151.txt ├── bctech2152.txt ├── bctech2153.txt ├── bctech2154.txt ├── bctech2155.txt ├── bctech2156.txt ├── bctech2157.txt └── desktop.ini ├── master dictionary ├── cleaned_negative_words.txt ├── cleaned_positive_words.txt ├── desktop.ini ├── negative-words.txt └── positive-words.txt ├── project Introduction ├── desktop.ini ├── myworkintro.ipynb ├── requirement.txt └── testassessment.ipynb ├── test assignment ├── Textanalysis.ipynb ├── dataextraction.ipynb ├── desktop.ini ├── readability_analysis_results.csv ├── sentiment_analysis.log ├── textanalysisoverflow.ipynb ├── textblob_sentiment_results.csv └── textual_analysis_metrics.xlsx └── visualization └── word_frequency_visualization.png /Input.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/rubydamodar/ProText-Analyzer/2e4f2b9c4de97aa79f3b48aa4fcf110999b2b89f/Input.xlsx -------------------------------------------------------------------------------- /Objective.docx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/rubydamodar/ProText-Analyzer/2e4f2b9c4de97aa79f3b48aa4fcf110999b2b89f/Objective.docx -------------------------------------------------------------------------------- /Output Data Structure.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/rubydamodar/ProText-Analyzer/2e4f2b9c4de97aa79f3b48aa4fcf110999b2b89f/Output Data Structure.xlsx -------------------------------------------------------------------------------- /StopWords/StopWords_Auditor.txt: -------------------------------------------------------------------------------- 1 | ERNST 2 | YOUNG 3 | DELOITTE 4 | TOUCHE 5 | KPMG 6 | PRICEWATERHOUSECOOPERS 7 | PRICEWATERHOUSE 8 | COOPERS 9 | -------------------------------------------------------------------------------- /StopWords/StopWords_Currencies.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/rubydamodar/ProText-Analyzer/2e4f2b9c4de97aa79f3b48aa4fcf110999b2b89f/StopWords/StopWords_Currencies.txt -------------------------------------------------------------------------------- /StopWords/StopWords_DatesandNumbers.txt: -------------------------------------------------------------------------------- 1 | HUNDRED | Denominations 2 | THOUSAND 3 | MILLION 4 | BILLION 5 | TRILLION 6 | DATE | Time related 7 | ANNUAL 8 | ANNUALLY 9 | ANNUM 10 | YEAR 11 | YEARLY 12 | QUARTER 13 | QUARTERLY 14 | QTR 15 | MONTH 16 | MONTHLY 17 | WEEK 18 | WEEKLY 19 | DAY 20 | DAILY 21 | JANUARY | Calendar 22 | FEBRUARY 23 | MARCH 24 | APRIL 25 | MAY 26 | JUNE 27 | JULY 28 | AUGUST 29 | SEPTEMBER 30 | OCTOBER 31 | NOVEMBER 32 | DECEMBER 33 | JAN 34 | FEB 35 | MAR 36 | APR 37 | MAY 38 | JUN 39 | JUL 40 | AUG 41 | SEP 42 | SEPT 43 | OCT 44 | NOV 45 | DEC 46 | MONDAY 47 | TUESDAY 48 | WEDNESDAY 49 | THURSDAY 50 | FRIDAY 51 | SATURDAY 52 | SUNDAY 53 | ONE | Numbers 54 | TWO 55 | THREE 56 | FOUR 57 | FIVE 58 | SIX 59 | SEVEN 60 | EIGHT 61 | NINE 62 | TEN 63 | ELEVEN 64 | TWELVE 65 | THIRTEEN 66 | FOURTEEN 67 | FIFTEEN 68 | SIXTEEN 69 | SEVENTEEN 70 | EIGHTEEN 71 | NINETEEN 72 | TWENTY 73 | THIRTY 74 | FORTY 75 | FIFTY 76 | SIXTY 77 | SEVENTY 78 | EIGHTY 79 | NINETY 80 | FIRST 81 | SECOND 82 | THIRD 83 | FOURTH 84 | FIFTH 85 | SIXTH 86 | SEVENTH 87 | EIGHTH 88 | NINTH 89 | TENTH 90 | I | Roman numerals 91 | II 92 | III 93 | IV 94 | V 95 | VI 96 | VII 97 | VIII 98 | IX 99 | X 100 | XI 101 | XII 102 | XIII 103 | XIV 104 | XV 105 | XVI 106 | XVII 107 | XVIII 108 | XIX 109 | XX -------------------------------------------------------------------------------- /StopWords/StopWords_Generic.txt: -------------------------------------------------------------------------------- 1 | ABOUT 2 | ABOVE 3 | AFTER 4 | AGAIN 5 | ALL 6 | AM 7 | AMONG 8 | AN 9 | AND 10 | ANY 11 | ARE 12 | AS 13 | AT 14 | BE 15 | BECAUSE 16 | BEEN 17 | BEFORE 18 | BEING 19 | BELOW 20 | BETWEEN 21 | BOTH 22 | BUT 23 | BY 24 | CAN 25 | DID 26 | DO 27 | DOES 28 | DOING 29 | DOWN 30 | DURING 31 | EACH 32 | FEW 33 | FOR 34 | FROM 35 | FURTHER 36 | HAD 37 | HAS 38 | HAVE 39 | HAVING 40 | HE 41 | HER 42 | HERE 43 | HERS 44 | HERSELF 45 | HIM 46 | HIMSELF 47 | HIS 48 | HOW 49 | IF 50 | IN 51 | INTO 52 | IS 53 | IT 54 | ITS 55 | ITSELF 56 | JUST 57 | ME 58 | MORE 59 | MOST 60 | MY 61 | MYSELF 62 | NO 63 | NOR 64 | NOT 65 | NOW 66 | OF 67 | OFF 68 | ON 69 | ONCE 70 | ONLY 71 | OR 72 | OTHER 73 | OUR 74 | OURS 75 | OURSELVES 76 | OUT 77 | OVER 78 | OWN 79 | SAME 80 | SHE 81 | SHOULD 82 | SO 83 | SOME 84 | SUCH 85 | THAN 86 | THAT 87 | THE 88 | THEIR 89 | THEIRS 90 | THEM 91 | THEMSELVES 92 | THEN 93 | THERE 94 | THESE 95 | THEY 96 | THIS 97 | THOSE 98 | THROUGH 99 | TO 100 | TOO 101 | UNDER 102 | UNTIL 103 | UP 104 | VERY 105 | WAS 106 | WE 107 | WERE 108 | WHAT 109 | WHEN 110 | WHERE 111 | WHICH 112 | WHILE 113 | WHO 114 | WHOM 115 | WHY 116 | WITH 117 | YOU 118 | YOUR 119 | YOURS 120 | YOURSELF 121 | YOURSELVES -------------------------------------------------------------------------------- /StopWords/StopWords_Geographic.txt: -------------------------------------------------------------------------------- 1 | UNITED | Geographic 2 | STATE 3 | NORTH 4 | SOUTH 5 | EAST 6 | NORTHEAST 7 | NORTHWEST 8 | SOUTHEAST 9 | SOUTHWEST 10 | WEST 11 | OCEAN 12 | SEA 13 | LAKE 14 | RIVER 15 | CREEK 16 | GULF 17 | MOUNTAIN 18 | STREET 19 | BOULEVARD 20 | BLVD 21 | PARKWAY 22 | CITY 23 | COUNTY 24 | COUNTRY 25 | PACIFIC 26 | ATLANTIC 27 | INDIAN 28 | MEDITERRANEAN 29 | COMMONWEALTH 30 | AMERICA 31 | AMERICAN 32 | YORK | Cities 33 | CHICAGO 34 | LAS 35 | VEGAS 36 | LOS 37 | ANGELES 38 | MILWAUKEE 39 | SUNNYVALE 40 | FREMONT 41 | CINCINNATI 42 | PHILADELPHIA 43 | MIAMI 44 | DALLAS 45 | FORT 46 | BOSTON 47 | HOUSTON 48 | WASHINGTON 49 | ATLANTA 50 | DETROIT 51 | SAN 52 | FRANSICO 53 | PHOENIX 54 | SEATTLE 55 | DIEGO 56 | MINNEAPOLIS 57 | MEMPHIS 58 | DENVER 59 | ST 60 | LOUIS 61 | PITTSBURGH 62 | MANHATTAN 63 | HOLLYWOOD 64 | COLUMBUS 65 | INDIANAPOLIS 66 | MUMBAI 67 | KARACHI 68 | ONTARIO 69 | TORONTO 70 | CAMBRIDGE 71 | DELHI 72 | SAO 73 | PAULO 74 | SHANGHAI 75 | MOSCOW 76 | SEOUL 77 | ISTANBUL 78 | TOKYO 79 | JAKARTA 80 | BEIJING 81 | LONDON 82 | LUXEMBOURG 83 | SINGAPORE 84 | REPUBLIC | Countries 85 | CHINA 86 | INDIA 87 | INDONESIA 88 | BRAZIL 89 | BRAZILIAN 90 | PAKISTAN 91 | BANGLADESH 92 | RUSSIA 93 | NIGERIA 94 | NOVA 95 | SCOTIA 96 | JAPAN 97 | MALAYSIA 98 | MEXICO 99 | MEXICAN 100 | PHILIPPINES 101 | VIETNAM 102 | GERMANY 103 | FRANCE 104 | KOREA 105 | SPAIN 106 | ARGENTINA 107 | BERMUDA 108 | COLUMBIA 109 | PUERTO 110 | CANADA 111 | CANADIAN 112 | AFRICA 113 | AFRICAN 114 | CHILE 115 | CHILEAN 116 | EUROPE 117 | EUROPEAN 118 | USA 119 | ITALY 120 | ITALIAN 121 | AUSTRALIA 122 | NETHERLANDS 123 | NORWAY 124 | PORTUGAL 125 | TAIWAN 126 | ARGENTINA 127 | SWITZERLAND 128 | SWISS 129 | SUISSE 130 | DENMARK 131 | CZECK 132 | HUNGARY 133 | FINLAND 134 | SCOTLAND 135 | COSTA 136 | RICA 137 | SWEDEN 138 | BELGIUM 139 | AUSTRIA 140 | TURKEY 141 | POLAND 142 | INDONESIA 143 | THAILAND 144 | VENEZUELA 145 | ASIA 146 | ZEALAND 147 | JAPANESE 148 | LATIN 149 | BRITISH 150 | CHINESE 151 | ALABAMA | States 152 | ALASKA 153 | ARIZONA 154 | ARKANSAS 155 | CALIFORNIA 156 | COLORADO 157 | CONNECTICUT 158 | DELAWARE 159 | FLORIDA 160 | GEORGIA 161 | HAWAII 162 | IDAHO 163 | ILLINOIS 164 | INDIANA 165 | IOWA 166 | KANSAS 167 | KENTUCKY 168 | LOUISIANA 169 | MAINE 170 | MARYLAND 171 | MASSACHUSETTS 172 | MICHIGAN 173 | MINNESOTA 174 | MISSISSIPPI 175 | MISSOURI 176 | MONTANA 177 | NEBRASKA 178 | NEVADA 179 | HAMPSHIRE 180 | JERSEY 181 | MEXICO 182 | NEW 183 | YORK 184 | OHIO 185 | OKLAHOMA 186 | OREGON 187 | PENNSYLVANIA 188 | RHODE 189 | ISLAND 190 | CAROLINA 191 | DAKOTA 192 | TENNESSEE 193 | TEXAS 194 | UTAH 195 | VERMONT 196 | VIRGINIA 197 | WASHINGTON 198 | WISCONSIN 199 | WYOMING 200 | -------------------------------------------------------------------------------- /Text Analysis.docx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/rubydamodar/ProText-Analyzer/2e4f2b9c4de97aa79f3b48aa4fcf110999b2b89f/Text Analysis.docx -------------------------------------------------------------------------------- /analysis result/analysis_results.csv: -------------------------------------------------------------------------------- 1 | URL_ID,positive_score,negative_score,polarity_score,subjectivity_score,avg_sentence_length,percentage_complex_words,fog_index,avg_words_per_sentence,complex_word_count,word_count,syllable_per_word,personal_pronouns,avg_word_length 2 | bctech2073,0.05,0.0,0.05,0.5590909090909091,13.0,56.41025641025641,27.764102564102565,13.0,44,78,1.8974358974358974,0,5.794871794871795 3 | bctech2074,0.19166666666666668,0.0,0.19166666666666668,0.5107142857142858,15.6,73.07692307692307,35.47076923076923,15.6,57,78,1.935897435897436,0,6.141025641025641 4 | bctech2075,0.19999999999999998,0.0,0.19999999999999998,0.19999999999999998,16.2,67.90123456790124,33.6404938271605,16.2,55,81,2.074074074074074,0,5.9753086419753085 5 | bctech2076,0.0,-0.08,-0.08,0.44000000000000006,15.0,68.0,33.2,15.0,51,75,2.2266666666666666,0,6.4 6 | bctech2077,0.12,0.0,0.12,0.38,15.8,77.21518987341773,37.20607594936709,15.8,61,79,2.1139240506329116,0,6.063291139240507 7 | -------------------------------------------------------------------------------- /analysis result/analysis_results.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/rubydamodar/ProText-Analyzer/2e4f2b9c4de97aa79f3b48aa4fcf110999b2b89f/analysis result/analysis_results.xlsx -------------------------------------------------------------------------------- /analysis result/finaltext_analysis_results.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/rubydamodar/ProText-Analyzer/2e4f2b9c4de97aa79f3b48aa4fcf110999b2b89f/analysis result/finaltext_analysis_results.xlsx -------------------------------------------------------------------------------- /analysis result/results.csv: -------------------------------------------------------------------------------- 1 | Positive Score,Negative Score,Polarity Score,Subjectivity Score,Average Word Length,Complex Word Count,Word Count,Personal Pronouns Count,Average Words Per Sentence 2 | 2,0,0.99999950000025,0.14285713265306196,3.6666666666666665,2,14,0,4.666666666666667 3 | -------------------------------------------------------------------------------- /analysis result/textual_analysis_results.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/rubydamodar/ProText-Analyzer/2e4f2b9c4de97aa79f3b48aa4fcf110999b2b89f/analysis result/textual_analysis_results.xlsx -------------------------------------------------------------------------------- /cleaned_articles/bctech2039.txt: -------------------------------------------------------------------------------- 1 | Title: Data Management - EGEAS - Blackcoffer Insights HomeOur Success StoriesData Management – EGEASOur Success StoriesITData Management – EGEASByAjay Bidyarthy-August 6, 20232676Client BackgroundClient:A leading tech firm USAIndustry Type:ITServices:SaaS, ProductsOrganization Size:100+Project ObjectiveTo extract various Reports given input files. Reports extracted are: PRODUCTION COST – ANNUAL UNITS REPORT, SYSTEM EMISSIONS ANNUAL REPORT, RPS CONSTRAINT – ANNUAL REPORT, RELIABILITY – ANNUAL REPORT, RESERVE – ANNUAL REPORT CAPACITY TOTALS ANNUAL REPORT. extract mentioned reports given .out files store respective .csv files.Project DescriptionWe given a bunch .out files various Reports available table format. need extract required reports given files store respective .csv files. A tool developed python order accomplish task.Our SolutionFrom .out file content extracted stored a list. Using regular expression, searched required report content. Another regular expression used mark end table content. Content two given regular expressions stored a dataframe stored respective .csv file.Project DeliverablesPython Scripts report a combined script could extract required Reports.Respective .csv files ReportsTools usedPython InterpreterLanguage/techniques usedLanguage Used: PythonLibraries Used: re, pandas, osSkills usedProgrammingProject SnapshotsContact DetailsHere contact details:Email: ajay@blackcoffer.comSkype: asbidyarthyWhatsApp: +91 9717367468Telegram: @asbidyarthyFor project discussions daily updates, would like use Slack, Skype, Telegram, Whatsapp? Please recommend, would work best you.Previous articleDesign develop PowerShell scriptNext articleData Management, ETL, Data AutomationAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSDesign develop solution anomaly detection classification problemsSeptember 16, 2022Management challenges future digitalization healthcare servicesDecember 2, 2020Artificial intelligence business: Separating real hypeSeptember 25, 2018Big Data Problem & SolutionsJuly 4, 2019Load moreRECOMMENDED INSIGHTSHealthcare AI ChatBot using LLAMA, LLM, LangchainWhat Creation Taking Creator?Data Studio Dashboard a data pipeline tool synced Podio...How COVID-19 impacting payment preferences? -------------------------------------------------------------------------------- /cleaned_articles/bctech2041.txt: -------------------------------------------------------------------------------- 1 | Title: Design develop Jenkins shared library - Blackcoffer Insights HomeOur Success StoriesDesign develop Jenkins shared libraryOur Success StoriesITDesign develop Jenkins shared libraryByAjay Bidyarthy-August 6, 20232701Client BackgroundClient:A leading tech firm USAIndustry Type:ITServices:SaaS, ProductsOrganization Size:100+The ProblemCreate Jenkins shared library following:validate AWS AMI creationcheck network rules exist aws EC2check security group aws EC2Our SolutionWe created a Jenkins shared library using AWS ec2 describe-images command help aws cli ami don’t exist describe-images throws errorWe created a Jenkins shared library using aws ec2 describe-network-acls validating comparing input name VPCWe created a Jenkins shared library using aws ec2 describe-instances validating checking input name SecurityGroups groupDeliverablesJenkins LibrariesTools usedVS Code IDEJenkinsAWSLanguage/techniques usedGrovvySkills usedJenkinsAWS ServerWeb Cloud Servers usedAWSProject SnapshotsProject VideoContact DetailsHere contact details:Email: ajay@blackcoffer.comSkype: asbidyarthyWhatsApp: +91 9717367468Telegram: @asbidyarthyFor project discussions daily updates, would like use Slack, Skype, Telegram, Whatsapp? Please recommend, would work best you.Previous articleDesign develop retool app wholecell.io Asana data using api’sNext articleDesign develop PowerShell scriptAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSAutoGPT SetupMay 10, 2023Impacts COVID 19 Streets Sides Food StallsNovember 6, 2021Deploy MERN google app engine, google cloud platformMay 16, 2021Transforming Healthcare SystemsApril 17, 2021Load moreRECOMMENDED INSIGHTSAn outlook healthcare year 2040, it...Marketing Analytics – care it?Healthcare AI ChatBot using LLAMA, LLM, LangchainLipsync Automation Celebrities Influencers -------------------------------------------------------------------------------- /cleaned_articles/bctech2042.txt: -------------------------------------------------------------------------------- 1 | Title: Design develop retool app wholecell.io Asana data using api’s - Blackcoffer Insights HomeOur Success StoriesDesign develop retool app wholecell.io Asana data using their...Our Success StoriesITDesign develop retool app wholecell.io Asana data using api’sByAjay Bidyarthy-August 6, 20232576Client BackgroundClient:A leading tech firm USAIndustry Type:ITServices:SaaS, ProductsOrganization Size:100+The ProblemCreate retool app wholecell.io Asana data using api’sOur SolutionWe created two table one table contain data wholecell.io platform another table contain data Assna.In wholecell.io table providing:Order idOrder statusOrder channelOrganizationLink OrderIn Assna Table providing following details:Id taskName taskResource typeResource_subtypeCallerPo-idAs client data wholecell Assna linked client search order PO-id Assna tableDeliverablesApp retoolTools usedRetoolLanguage/techniques usedJavaScriptSkills usedRetoolAPI integrationJavaScriptWhat technical Challenges Faced Project ExecutionApi providing required details according client requirement less options data pre-processing retool javascriptHow Technical Challenges SolvedWe fetched details one api provide id api using JavaScript done using javascript promise methodWe also string manipulation get data according client requirementContact DetailsHere contact details:Email: ajay@blackcoffer.comSkype: asbidyarthyWhatsApp: +91 9717367468Telegram: @asbidyarthyFor project discussions daily updates, would like use Slack, Skype, Telegram, Whatsapp? Please recommend, would work best you.Previous articleDesign develop a retool app will show stock crypto related information using IEX APINext articleDesign develop Jenkins shared libraryAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSDeploy view React app(Nextjs) cloud VM GCP,...August 8, 2023How AI will help Defense Power a country?June 26, 2021Role Big Data Cyber Security: A Shotgun Against Rising...June 11, 2017Why a severe immunological inflammatory explosion those...March 30, 2020Load moreRECOMMENDED INSIGHTSHow Retail Industry Drive Value Big Data?Changing landscape emerging trends Indian IT/ITeS Industry.Impacts COVID 19 Food productsOff-Page SEO -------------------------------------------------------------------------------- /cleaned_articles/bctech2043.txt: -------------------------------------------------------------------------------- 1 | Title: Design develop a retool app will show stock crypto related information using IEX API - Blackcoffer Insights HomeOur Success StoriesDesign develop a retool app will show stock crypto...Our Success StoriesBanking, Financials, Securities, InsuranceDesign develop a retool app will show stock crypto related information using IEX APIByAjay Bidyarthy-August 6, 20232584Client BackgroundClient:A leading fintech firm USAIndustry Type:FinanceServices:Crypto, financial services, banking, trading, stock marketsOrganization Size:100+The ProblemCreate a retool app will show stock crypto related information using IEX APIOur SolutionCreated a flask web application following features pages:Page 1 (Home page)– Show a Stock & Crypto Search Bar will show relevant option IEX API via ticker search. Upon submit, user will taken “Ticker Page”– List 10 top trending stocks category (link click ticker page)(logo, Stock ticker, company name, stock price, % change.Mega CapLarge CapMid CapSmall CapMicro CapPage 2 (Ticker Page)-Show Company Data – (Ticker, Company Name, Logo, Market Cap, corporate data (employees, CEO, HQ, Founded, Website)-Stock Price Chart – 1 year chart, daily.-Stock Price Volume – Weekly average 20 weeks-Recent News – list 25 recent articlesDeliverablesDeployed flask web application AWSTools usedVS Code IDENginxLanguage/techniques usedPythonSkills usedAPI IntegrationPythonAWS ServerNginxWeb Cloud Servers usedAWSWhat technical Challenges Faced Project ExecutionThere lots pre-processing required create application per client requirementHow Technical Challenges SolvedWe shifted application retool python flask application python programming language allow pre-process data per requirementProject SnapshotsProject website urlwww.stocks.bullish.studioProject VideoContact DetailsHere contact details:Email: ajay@blackcoffer.comSkype: asbidyarthyWhatsApp: +91 9717367468Telegram: @asbidyarthyFor project discussions daily updates, would like use Slack, Skype, Telegram, Whatsapp? Please recommend, would work best you.Previous articleCRM (Monday.com, Make.com) Data Warehouse Klipfolio DashboardNext articleDesign develop retool app wholecell.io Asana data using api’sAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSEntertainment Music Player User Analytics RecommendationsMarch 23, 2021OCR – Extracting Information Scanned DocumentsApril 18, 2020Do Social Media Owned Meta?January 17, 2022Medical ClassificationSeptember 16, 2022Load moreRECOMMENDED INSIGHTSData Engineering Management tool (Airbyte) custom data connectors to...Dockerize AWS Lambda serverless architectureThe impact Metaverse financial servicesChatbot using VoiceFlow -------------------------------------------------------------------------------- /cleaned_articles/bctech2046.txt: -------------------------------------------------------------------------------- 1 | Title: Qualtrics API integration using Python - Blackcoffer Insights HomeOur Success StoriesQualtrics API integration using PythonOur Success StoriesQualtrics API integration using PythonByAjay Bidyarthy-August 5, 20232631Client BackgroundClient:A leading tech firm USAIndustry Type:ITServices:SaaS, ProductsOrganization Size:100+The ProblemAPI Integration read/write data SQL tables online application.Our SolutionTo write api qualtrics sql server using python programming language.Solution ArchitectureFig. System ArchitectureDeliverablesPython SoftwareDocumentationTools usedPythonQualtricsModels usedPandasRequestsnumpyZipfileiopyodbcSkills usedExtract Transfer LoadDatabases usedSQL ServerWhat technical Challenges Faced Project ExecutionDuring project execution, faced following challenges:After data integration, content file readable.Mapping values required columns.How Technical Challenges SolvedTo solve technical challenges, provided following solutions follow:To get content CSV format integration used Io module get text content.To get mapping values created CSV file store record fetch record SQl.Business ImpactUsing script client fetch Qualtrics data SQL server automatically every 1 hour.Project SnapshotsFig. Data CSV FormatFig. Data Table formFig. SQL dataProject website urlGithub: https://github.com/AjayBidyarthy/Richi-S-apiProject VideoContact DetailsHere contact details:Email: ajay@blackcoffer.comSkype: asbidyarthyWhatsApp: +91 9717367468Telegram: @asbidyarthyFor project discussions daily updates, would like use Slack, Skype, Telegram, Whatsapp? Please recommend, would work best you.Previous articleDesign develop MLops framework Data-centric AINext articleNER Task using BERT data XML-formatAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSEffective Management Social Media Data Extraction: Strategies Authentication, Security,...March 17, 2024COVID-19 Impact Hospitality IndustryMay 1, 2020Deploy Nodejs app a cloud VM GCP, AWS,...August 8, 2023Replacing existing pavement roads, parking lots sidewalks pavement made...July 17, 2019Load moreRECOMMENDED INSIGHTSRise Chatbots impact customer support the...React Native Apps Development PortfolioAuvik, Connectwise integration GrafanaHow protect future data privacy? -------------------------------------------------------------------------------- /cleaned_articles/bctech2048.txt: -------------------------------------------------------------------------------- 1 | Title: NLP-based Approach Data Transformation - Blackcoffer Insights HomeOur Success StoriesNLP-based Approach Data TransformationOur Success StoriesITNLP-based Approach Data TransformationByAjay Bidyarthy-July 29, 20232744Client BackgroundClient:A leading tech firm USAIndustry Type:ITServices:SaaS, ProductsOrganization Size:100+The ProblemPerforming Readability Quality testing text corpus text filesOur SolutionThe intention create a tool/system consume text files a given csv file a path text files csv file tool able read files one one could perform tests analysis text data output results a csv format presenting metrics.In order achieve goal created a Python-based ready-to-use code will read text files presented given csv files perform 14 different evaluations text data save results a excel csv based format.Solution ArchitectureDeliverablesThe final deliverable tool/system/code processing evaluation text.Language/techniques usedPythonNatural Language processing technique used text evaluationSkills usedPython ProgrammingWhat technical Challenges Faced Project ExecutionThe architecture solution project problem statement simple, challenges faced execution project.Contact DetailsHere contact details:Email: ajay@blackcoffer.comSkype: asbidyarthyWhatsApp: +91 9717367468Telegram: @asbidyarthyFor project discussions daily updates, would like use Slack, Skype, Telegram, Whatsapp? Please recommend, would work best you.Previous articleAn ETL tool pull data Shiphero Google Bigquery Data WarehouseNext articleDesign develop MLops framework Data-centric AIAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSLipsync Automation Celebrities InfluencersSeptember 5, 2021Transforming Healthcare SystemsApril 17, 2021Deploy Nodejs app a cloud VM GCP, AWS,...August 8, 2023How Telehealth Telemedicine helping people fight against COVID-19April 28, 2022Load moreRECOMMENDED INSIGHTSUsing People Analytics Drive Business PerformanceAnalyzing Impact Female CEO Appointments Company Stock PricesEmbedding care robots society practice: Socio-technical considerationsThe Metaverse Implications Digital Future. -------------------------------------------------------------------------------- /cleaned_articles/bctech2052.txt: -------------------------------------------------------------------------------- 1 | Title: Data CRM via Zapier Google Sheets (Dynamic) PowerBI - Blackcoffer Insights HomeOur Success StoriesData CRM via Zapier Google Sheets (Dynamic) PowerBIOur Success StoriesEnergyData CRM via Zapier Google Sheets (Dynamic) PowerBIByAjay Bidyarthy-July 29, 20232742Client BackgroundClient:A leading solar panel firm USAIndustry Type:EnergyServices:Solar PanelOrganization Size:500+The ProblemSolar Panel organization America wants keep track sales data. want see leadership dashboard organization terms sales. also want keep track campaigns leads generated sources campaigns. want keep track sales data different sources.Our SolutionFirst, fetch data CRM PowerBI. Clean data CRM using DAX perform calculations data. Using cleaned data, build KPI PowerBI.Solution ArchitectureTo complete project, follow following data flow pipeline:Data CRM 🡪 Zapier 🡪 Google Sheet (Dynamic) 🡪PowerBILanguage/techniques usedPowerBI, DAX LanguageSkills usedCRM, Zapier , PowerBI, Google SheetWhat technical Challenges Faced Project ExecutionChallenges Faced Project Execution :Fetching data CRMUnclean DataMerging DataHow Technical Challenges SolvedSolution:To Fetch data CRM. used Zapier. connector two applications whenever a particular incident happen will populate another application. use Zapier connect CRM Google sheets whenever a new lead will change modified data will stored google sheets.Data google sheets uncleaned. First, connect Google sheet PowerbI perform EDA clean data using DAX language.Using merging two tables ONE-ON-ONE schema solve duplicate entries a particular lead PowerBI.Business ImpactUsing Dashboard client make important decisions like campaign getting a greater number leads leads many actually a Sale. keep track sales leadership employee month term sales.Project SnapshotsCRMZapierDashboardProject VideoContact DetailsHere contact details:Email: ajay@blackcoffer.comSkype: asbidyarthyWhatsApp: +91 9717367468Telegram: @asbidyarthyFor project discussions daily updates, would like use Slack, Skype, Telegram, Whatsapp? Please recommend, would work best you.Previous articleData Warehouse Google Data Studio (Looker) DashboardNext articleRecommendation Engine Insurance Sector Expand Business Rural AreaAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSELK Stack – Elastic QueriesAugust 20, 2021Text Speech, htmlMay 10, 2019Monday.com KPI Dashboard manage, view, generate insights from...July 29, 2023Deploy Nodejs app a cloud VM GCP, AWS,...August 8, 2023Load moreRECOMMENDED INSIGHTSSports Prediction Model Multiple Sports LeaguesCar Parking Management SystemWill ever colonize outer space?COVID-19 Vs Indian Economy -------------------------------------------------------------------------------- /cleaned_articles/bctech2054.txt: -------------------------------------------------------------------------------- 1 | Title: CRM, Monday.com via Zapier Power BI Dashboard - Blackcoffer Insights HomeOur Success StoriesCRM, Monday.com via Zapier Power BI DashboardOur Success StoriesEnergyCRM, Monday.com via Zapier Power BI DashboardByAjay Bidyarthy-July 29, 20232847Client BackgroundClient:A leading solar panel firm USAIndustry Type:EnergyServices:Solar PanelOrganization Size:200+Project DescriptionMohsin Solar Panel Company. setup CRMs that. wanted use CRMs data want visualize leads PowerBIOur SolutionFirst, check CRMs thoroughly understand work culture company. easy fetch data PowerBI using API key. fetch new leads CRMs used Zapier. limitation Zapier cannot fetch historical data spreadsheet. download data CRMs fetch spreadsheet. new leads created zaps every instance. connect spreadsheet PowerBI clean data accordingly. Using data, build KPIs according client need.Tools usedAPI , Zapier , Spreadsheet , PowerBILanguage/techniques usedM language , DAXSkills usedAPI , M language , DAX , PowerBIWhat technical Challenges Faced Project Execution?First challenge fetch data CRMs using API key. Data getting uncleaned able fetch data. multiple pages CRMs will able fetch data pages.How Technical Challenges SolvedTechnical challenge project extract data CRMs. used Zapier connector CRMs spreadsheet. limitation Zapier will fetch historical data CRMs. solve download historical data CRMs append spreadsheet using. fetch new leads spreadsheet using Zapier. data historical new lead will pushed Zapier.Then fetch data PowerBI cleaning data. using cleaned data, build KPIs client according requirements.Business ImpactClient will able keep track company data PowerBI helps make decisions accordingly.Project SnapshotsCRMsZapierPowerBI DashboardProject VideoContact DetailsHere contact details:Email: ajay@blackcoffer.comSkype: asbidyarthyWhatsApp: +91 9717367468Telegram: @asbidyarthyFor project discussions daily updates, would like use Slack, Skype, Telegram, Whatsapp? Please recommend, would work best you.Previous articleMonday.com KPI Dashboard manage, view, generate insights CRM dataNext articleData Warehouse Google Data Studio (Looker) DashboardAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSBlockchain FintechSeptember 14, 2019How advanced analytics redefining banking?June 1, 2019On-Page SEOSeptember 19, 2020Audify Music Player Website MERN StackMarch 14, 2021Load moreRECOMMENDED INSIGHTSGoogle Local Service Ads (LSA) Leads DashboardAI Conversational Bot using RASAHow Big Data & Analytics change healthcare sector in...Coronavirus: Impact Hospitality Industry -------------------------------------------------------------------------------- /cleaned_articles/bctech2066.txt: -------------------------------------------------------------------------------- 1 | Title: AI agent development Deployment Jina AI - Blackcoffer Insights HomeOur Success StoriesAI agent development Deployment Jina AIOur Success StoriesITAI agent development Deployment Jina AIByAjay Bidyarthy-July 24, 20232639Client BackgroundClient:A leading tech firm EuropeIndustry Type:ITServices:IT ConsultingOrganization Size:100+The ProblemThe client’s object create AI agents website, end-users will utilize many tasks. client recommendations models utilized.Our SolutionCreated a feasible models list complements client’s requirement ahead executed Executor code every model compatibility JinaAI deployment. implementing Executor codes, I created a Flow connect every executor deployed successfully.DeliverablesSuccessfully delivered executable deployed models Jina AiTools usedJina AI, VSCode, HuggingFaceLanguage/techniques usedPythonModels usedWhisper, Stable Diffusion, GPT3, Codex, YOLO, CoquiAI, PDF SegmentorSkills usedPython, Model APIsDatabases usedJinaAI CloudWhat technical Challenges Faced Project ExecutionThere minute challenges, deployment issues Execution issuesHow Technical Challenges SolvedI resolved issues effectively long hours understanding concept JinaAI a new growing technology many forums solve errors issues.Project SnapshotsProject VideoContact DetailsHere contact details:Email: ajay@blackcoffer.comSkype: asbidyarthyWhatsApp: +91 9717367468Telegram: @asbidyarthyFor project discussions daily updates, would like use Slack, Skype, Telegram, Whatsapp? Please recommend, would work best you.Previous articleGolden Record – A knowledge graph database approach unfold discovery using Neo4jNext articleAI Solutions Foreign Exchange – Automated Algo Trading ToolAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSAn ETL solution Internet Publishing firmJuly 26, 2023Which one better AI big data?July 19, 2021Big Data Analytics IoT Oil Gas IndustrySeptember 10, 2018Coronavirus impact energy marketsMay 1, 2020Load moreRECOMMENDED INSIGHTSImpacts COVID 19 Food productsImpact COVID-19 pandemic office space co-working industries.Building Custom TFLite Models Benchmarking VOXL2 ChipsHow people diverted Telehealth services telemedicine? -------------------------------------------------------------------------------- /cleaned_articles/bctech2069.txt: -------------------------------------------------------------------------------- 1 | Title: Create a Knowledge Graph Provide Real-time Analytics, Recommendations, a Single Source Truth - Blackcoffer Insights HomeOur Success StoriesCreate a Knowledge Graph Provide Real-time Analytics, Recommendations, a Single...Our Success StoriesITRetail & Supply ChainCreate a Knowledge Graph Provide Real-time Analytics, Recommendations, a Single Source TruthByAjay Bidyarthy-July 22, 20232587Client BackgroundClient:A leading tech firm USAIndustry Type:RetailServices:Retail BusinessOrganization Size:100+The ProblemThe Client using NoSql Database slow provide real-time response complex queries. data many Connections difficult represent NoSQL Relational Databases.Our SolutionCreate a Knowledge Graph Provide Real-time Analytics Recommendations using Machine Learning.Solution ArchitectureNeo4j Installed a Cloud VM based Linodes.DeliverablesKnowledge graphs Data Pipelines used Populate Graph.API’s Perform CRUD operations real-time.Tools usedNeo4jPostmanLanguage/techniques usedPythonJSONModels usedNode-Relationship modelSkills usedProgrammingData EngineeringData AnalyticsDatabases usedNeo4jWeb Cloud Servers usedLinodeWhat technical Challenges Faced Project ExecutionIntegration Firestore Neo4j without native integration method driver.How Technical Challenges SolvedThe challenge solved using api retrieve data Firestore.Project SnapshotsContact DetailsHere contact details:Email: ajay@blackcoffer.comSkype: asbidyarthyWhatsApp: +91 9717367468Telegram: @asbidyarthyFor project discussions daily updates, would like use Slack, Skype, Telegram, Whatsapp? Please recommend, would work best you.Previous articleAdvanced AI Thermal Person DetectionNext articleAdvanced AI Trading AutomationAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSHow Big Data Help Finance Growth of...July 19, 2021Design develop retool app wholecell.io Asana data using...August 6, 2023How Retail Industry Drive Value Big Data?July 25, 2017Securing Sensitive Financial Data Privacy-Preserving Machine Learning Predictive AnalyticsAugust 25, 2024Load moreRECOMMENDED INSIGHTSData science – Create Tailored algorithmsIs big data AI?Travel Tourism OutlookHow robots help e-learning platforms? -------------------------------------------------------------------------------- /cleaned_articles/bctech2070.txt: -------------------------------------------------------------------------------- 1 | Title: Advanced AI Thermal Person Detection - Blackcoffer Insights HomeOur Success StoriesAdvanced AI Thermal Person DetectionOur Success StoriesInfrastructure & Real EstateProduction & ManufacturingAdvanced AI Thermal Person DetectionByAjay Bidyarthy-July 22, 20232635Client BackgroundClient:A leading tech firm Middle EastIndustry Type:SecurityServices:Security servicesOrganization Size:100+The ProblemDetect a Person thermal image videos. model created told us client.Our SolutionUse Deeplearning Computer Vision train model custom dataset get results.Solution ArchitectureLinux 22.04Nvidiva RTX 3080DeliverablesTrained modelTools usedLabelimgYolov7COCO2JSONLanguage/techniques usedPythonModels usedYolov7Skills usedDeeplearningComputer visionProgrammingContact DetailsHere contact details:Email: ajay@blackcoffer.comSkype: asbidyarthyWhatsApp: +91 9717367468Telegram: @asbidyarthyFor project discussions daily updates, would like use Slack, Skype, Telegram, Whatsapp? Please recommend, would work best you.Previous articleAdvanced AI Road Cam Threat DetectionNext articleCreate a Knowledge Graph Provide Real-time Analytics, Recommendations, a Single Source TruthAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSCreate a Knowledge Graph Provide Real-time Analytics, Recommendations, a...July 22, 2023An AI ML-based web application detects correctness text...July 8, 2022Blockchain PaymentsSeptember 7, 2019How Connect a Domain Install WordPress Microsoft AzureFebruary 15, 2020Load moreRECOMMENDED INSIGHTSWhat difference Artificial Intelligence, Machine Learning, Statistics, and...Algorithmic trading multiple commodities markets, like Forex, Metals, Energy, etc.An app updating email id user and...AI-driven data analysis AI tool using Langchain a leading real... -------------------------------------------------------------------------------- /cleaned_articles/bctech2071.txt: -------------------------------------------------------------------------------- 1 | Title: Advanced AI Road Cam Threat Detection - Blackcoffer Insights HomeOur Success StoriesAdvanced AI Road Cam Threat DetectionOur Success StoriesInfrastructure & Real EstateProduction & ManufacturingAdvanced AI Road Cam Threat DetectionByAjay Bidyarthy-July 22, 20232613Client BackgroundClient:A leading tech firm Middle EastIndustry Type:SecurityServices:Security servicesOrganization Size:100+The ProblemDetect threat level accidents a Pedestrian a Car.Our SolutionUse Deeplearning Computer vision logic detect threat level defined Client.Solution ArchitectureLinux 22.04DeliverablesProgram detects threat level.Pretrained model.Tools usedYolov7DEEPSORTOpencvLanguage/techniques usedPythonModels usedYolov7Skills usedProgrammingComputer VisionDeep learningWhat technical Challenges Faced Project ExecutionIntegration Object tracking algorithm Object detection algorithm.Writing logic detect threat level.How Technical Challenges SolvedThe technical challenge sorted testing, experimenting later finding modifying already existing repository use a baseline code integration.Contact DetailsHere contact details:Email: ajay@blackcoffer.comSkype: asbidyarthyWhatsApp: +91 9717367468Telegram: @asbidyarthyFor project discussions daily updates, would like use Slack, Skype, Telegram, Whatsapp? Please recommend, would work best you.Previous articleAdvanced AI Pedestrian Crossing SafetyNext articleAdvanced AI Thermal Person DetectionAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSDatabase Normalization & Segmentation Google Data Studio Dashboard InsightsFebruary 27, 2022Streamlined Equity Waterfall Calculation Deal Management SystemMarch 16, 2024Data Management ServicesSeptember 11, 2020Easy Database AccessJune 8, 2019Load moreRECOMMENDED INSIGHTSInterpret Coefficients Regression ModelsiOS Mobile Applications PortfolioDriving Insights Largest Community Investors TradersSteps Meta-Analysis -------------------------------------------------------------------------------- /cleaned_articles/bctech2072.txt: -------------------------------------------------------------------------------- 1 | Title: Advanced AI Pedestrian Crossing Safety - Blackcoffer Insights HomeOur Success StoriesAdvanced AI Pedestrian Crossing SafetyOur Success StoriesInfrastructure & Real EstateProduction & ManufacturingAdvanced AI Pedestrian Crossing SafetyByAjay Bidyarthy-July 22, 20232621Client BackgroundClient:A leading tech firm Middle EastIndustry Type:SecurityServices:Security servicesOrganization Size:100+The ProblemTraffic Signals inefficient even cars pedestrians road still works a timer stops traffic pedestrian unnecessarily.Our SolutionWe provide a Computer vision-logic Manipulate traffic signal work turns red x number pedestrians waiting cross signal.Solution ArchitectureYolov7 pose estimationOpencvDeliverablesThe program Detects Pedestrians Gives alerts traffic Signals turn Red stay Green.Yolov7 pose model weightsTools usedYolov7OpencvLanguage/techniques usedPythonComputer VisionModels usedYolov7 Pose EstimationSkills usedProgrammingComputer VisionDeep LearningWhat technical Challenges Faced Project ExecutionThere existing solution create logic scratch.How Technical Challenges SolvedResearching Computer Vision. Learning new Techniques Experimentation.Project SnapshotsContact DetailsHere contact details:Email: ajay@blackcoffer.comSkype: asbidyarthyWhatsApp: +91 9717367468Telegram: @asbidyarthyFor project discussions daily updates, would like use Slack, Skype, Telegram, Whatsapp? Please recommend, would work best you.Previous articleAdvanced AI Handgun DetectionNext articleAdvanced AI Road Cam Threat DetectionAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSMedical ClassificationSeptember 16, 2022Methodology ETL Discovery Tool using LLMA, OpenAI, LangchainFebruary 27, 2024Marketing Analytics Solution, a Big Data ApproachMay 1, 2019Global Economy effected CoronavirusApril 15, 2020Load moreRECOMMENDED INSIGHTSHow lead a project a team without technical...Data Studio Dashboard a data pipeline tool synced Podio...Data Warehouse Google Data Studio (Looker) DashboardRole Big Data Cyber Security: A Shotgun Against Rising... -------------------------------------------------------------------------------- /cleaned_articles/bctech2073.txt: -------------------------------------------------------------------------------- 1 | Title: Advanced AI Handgun Detection - Blackcoffer Insights HomeOur Success StoriesAdvanced AI Handgun DetectionOur Success StoriesInfrastructure & Real EstateITProduction & ManufacturingAdvanced AI Handgun DetectionByAjay Bidyarthy-July 21, 20232700Client BackgroundClient:A leading tech firm Middle EastIndustry Type:SecurityServices:Security servicesOrganization Size:100+The ProblemDetecting Handguns images videos.Our SolutionWe use Yolov7 instance segmentation model detect provide coordinates handguns.Solution ArchitectureLinux 22.04YoloDeliverablesTrained model yolov7 instance segmentationTools usedOpenimagesRoboflowYolov7Language/techniques usedPythonModels usedYolov7_maskSkills usedDeeplearningProgrammingWhat technical Challenges Faced Project ExecutionRetrieving handgun images bulk opensource.How Technical Challenges SolvedFound Openimages dataset good amount required imagesContact DetailsHere contact details:Email: ajay@blackcoffer.comSkype: asbidyarthyWhatsApp: +91 9717367468Telegram: @asbidyarthyFor project discussions daily updates, would like use Slack, Skype, Telegram, Whatsapp? Please recommend, would work best you.Previous articleUsing Graph Technology Create Single Customer View.Next articleAdvanced AI Pedestrian Crossing SafetyAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSAdvanced AI Pedestrian Crossing SafetyJuly 22, 2023What future mobile apps?February 12, 2021Off-Page SEOSeptember 18, 2020Marbles Stimulation using pythonAugust 30, 2021Load moreRECOMMENDED INSIGHTSNew Jersey Based Micro Business Sentiment AnalysisDesign develop PowerShell scriptGoogle LSA API Data Automation DashboardingAI Bot Driven GraphDB Neo4j a Leading Healthcare Tech... -------------------------------------------------------------------------------- /cleaned_articles/bctech2074.txt: -------------------------------------------------------------------------------- 1 | Title: Using Graph Technology Create Single Customer View. - Blackcoffer Insights HomeOur Success StoriesUsing Graph Technology Create Single Customer View.Our Success StoriesFast Moving Consumer GoodsRetail & Supply ChainUsing Graph Technology Create Single Customer View.ByAjay Bidyarthy-July 21, 20232641Client BackgroundClient:A leading retail firm NewzealandIndustry Type:RetailServices:Retail businessOrganization Size:100+The ProblemCompanies face issue a Single customer various rows slightly different information database. causes unwanted duplication inaccurate statistics. also results inaccurate ad targeting financial loss.Our SolutionWe leverage graph technology create a single customer view using Complex cypher queries Graph Algorithms.Solution ArchitectureWe Azure VM installed Neo4j Database. Deployment architecture a single Instance using Community version software.DeliverablesPopulated Neo4j Database.Required Cypher Queries.Tools usedNeo4jGraphlyticsLanguage/techniques usedJavaCypher QueryModels usedNode-Relationship modelSkills usedData AnalyticsData EngineeringData ScienceDatabases usedNeo4jWeb Cloud Servers usedAZUREWhat technical Challenges Faced Project ExecutionOnly 1 Difficulty faced Project migrate data Elasticsearch Neo4j.How Technical Challenges SolvedResearch Experimentation.Project SnapshotsContact DetailsHere contact details:Email: ajay@blackcoffer.comSkype: asbidyarthyWhatsApp: +91 9717367468Telegram: @asbidyarthyFor project discussions daily updates, would like use Slack, Skype, Telegram, Whatsapp? Please recommend, would work best you.Previous articleCar Detection Satellite ImagesNext articleAdvanced AI Handgun DetectionAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSData CRM via Zapier Google Sheets (Dynamic) PowerBIJuly 29, 2023How access Amazon Seller Central Vendor Central data in...March 3, 2021Advantages Disadvantages E-learning COVID-19 students and...December 7, 2021How Artificial Intelligence deliver real value companies?October 15, 2018Load moreRECOMMENDED INSIGHTSIntegration video-conferencing data existing web appReplacing existing pavement roads, parking lots sidewalks pavement made...Transform API SDK library widgetAI, ML, IoT driven Entry Management Monitoring -------------------------------------------------------------------------------- /cleaned_articles/bctech2084.txt: -------------------------------------------------------------------------------- 1 | Title: Trading Bot FOREX - Blackcoffer Insights HomeOur Success StoriesTrading Bot FOREXOur Success StoriesBanking, Financials, Securities, InsuranceTrading Bot FOREXByAjay Bidyarthy-December 31, 20223111Client BackgroundClient:A Leading Trading Firm USAIndustry Type:FinanceServices:Trading, ConsultingOrganization Size:100+The ProblemAutomate trading MT4 terminal forex certain conditions met, end trade best exit point.Save mt4 forex data a instrument live every tick.Our SolutionUse PyTrader log trading system (mt4) 2 brokers.Use live prices identify prices diverge.Buy one currency broker 1, sell currency broker 2.Hold prices come back together.Coded a MQL4 script will save tick data (bid, ask, open, high, low, close) instrument activeSolution ArchitectureDeliverablesPython Script Automate two Meta Trader 4 terminals, trade conditions true break trade a exit point.A MQL4 Sript will Save Live tick data (Bid, Ask, Spread, Open, High, Low, Close) a CSV file.Tools usedPyTradernumpypandasLanguage/techniques usedPython(Automation)Mql4(To save tick data)Business ImpactClient requirements automate forex trading strategy Meta Trader4 terminal, doesn’t bother trading anymore, Python script designed it, plus offers a safe exit point Ongoing Trades, saved client’s money time.Previous articlePython model analysis sector-specific stock ETFs investment purposesNext articleAlgorithmic trading multiple commodities markets, like Forex, Metals, Energy, etc.Ajay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSContinued Demand SustainabilityNovember 30, 2019Predictive Modelling, AI, ML Dashboards Power BIJune 26, 2021Recommendation Engine Insurance Sector Expand Business Rural...July 29, 2023Can robots tackle late-life loneliness?December 2, 2020Load moreRECOMMENDED INSIGHTSAdvance Analytics Refocusing ProfitsPrediction Model Online CasinoHow Artificial Intelligence deliver real value companies?ETL Pipeline -------------------------------------------------------------------------------- /cleaned_articles/bctech2088.txt: -------------------------------------------------------------------------------- 1 | Title: Design develop solution anomaly detection classification problems - Blackcoffer Insights HomeOur Success StoriesDesign develop solution anomaly detection classification problemsOur Success StoriesBanking, Financials, Securities, InsuranceITDesign develop solution anomaly detection classification problemsByAjay Bidyarthy-September 16, 20222790Client BackgroundClient:A Leading Tech Firm USAIndustry Type:IT ConsultingServices:Software, ConsultingOrganization Size:100+Project DescriptionWe need create a notebook solutions binary classification-related anomaly detection problems. need use machine learning deep learning models greater 90% accuracy.Our SolutionWe created a notebook anomaly detection. used 10 15 machine learning deep learning models 3 different types auto encoder models giving greater 90% accuracy. trained 3 models one classification data anomalies evaluated trained models test data.Project DeliverablesA notebook solutions anomaly detection related classification problems accuracy 90%.Tools usedGoogle colab notebooks, Tensorflow, Google driveLanguage/techniques usedPython programming language, Machine learning, Deep learning, Data analysis Data visualization.Models usedAuto Encoder Variational Auto EncoderSkills usedPython, Data Analysis, Data visualization, Machine learning, Deep learning.Databases usedMS ExcelWhat technical Challenges Faced Project ExecutionMost anomaly detection models work regression type data problem classification problem need deal classification data.Getting high accuracy also a tough challenge us a models work well anomaly detection related classification problems.How Technical Challenges SolvedSo limited models problem used classification models like Autoencoders, Isolation forest one class svm.Only Autoencoder giving high accuracy worked different types autoencoders like variational autoencoder normal autoencoder.Project SnapshotsPrevious articleAn ETL Solution Currency Data Google Big QueryNext articleDesign & Develop BERT Question Answering model explanations visualizationAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSStreamlined Integration: Interactive Brokers API Python Desktop Trading ApplicationMarch 17, 2024COVID-19: countries responding?April 29, 2020Impact COVID-19 Engineering Medical College pandemic...December 7, 2021Big Data Analytics HealthcareJuly 19, 2019Load moreRECOMMENDED INSIGHTSRising cities impact economy, environment, infrastructure,...Key Audit Matters Predictive ModelingIoT & AI/ML Solution Gas StationsData Analytics Solution Hospitality Industry -------------------------------------------------------------------------------- /cleaned_articles/bctech2092.txt: -------------------------------------------------------------------------------- 1 | Title: Transform API SDK library widget - Blackcoffer Insights HomeOur Success StoriesTransform API SDK library widgetOur Success StoriesHealthcareITTransform API SDK library widgetByAjay Bidyarthy-September 15, 20222607Client BackgroundClient:A Leading Tech Firm USAIndustry Type:ITServices:Consulting, Marketing, HealthtechOrganization Size:500+Project ObjectiveConvert API documentation SDK library widget. Expected deliverables SDK library widgets forWeb appsiOS appsAndroid AppsProject DescriptionAPI documentation available a tool allows customers type medication find cheapest price near them. partners want site, currently using API documentation would like ultimately able send embeddable widget incorporates tool siteOur SolutionWe created a flutter widget uses SDK libraries allows customer type medication find cheapest price near them.This widget embedded web, android IOS applicationsProject Deliverables1)SDK Library/Widget2)Sample flutter applicationTools usedFlutterLanguage/techniques usedDartSkills used1)Knowledge dart language2)flutter app developingWhat technical Challenges Faced Project Execution1 )Problems fetching details drugs pharmacies2) Showing details drugs pharmacies widgetHow Technical Challenges SolvedAll technical challenges solved proper communication client logical analyzing dataProject SnapshotsProject Videohttps://www.youtube.com/watch?v=MyNK_DPtsKA&ab_channel=BlackcofferPrevious articleIntegration a product a cloud-based CRM platformNext articleAn agent-based model a Virtual Power Plant (VPP)Ajay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSPrediction Model Online CasinoApril 5, 2021How Political Leaders will Shape Tomorrow using Big Data & AnalyticsApril 15, 2019Design develop Jenkins shared libraryAugust 6, 2023Streamlined Equity Waterfall Calculation Deal Management SystemMarch 16, 2024Load moreRECOMMENDED INSIGHTSDriving Insights Largest Community Investors TradersPower BI Dashboard Operations, Transactions, Marketing Data, embedding the...Rise Cybercrime Effect upcoming FutureThe workflow a Machine Learning / Artificial Intelligence project -------------------------------------------------------------------------------- /cleaned_articles/bctech2093.txt: -------------------------------------------------------------------------------- 1 | Title: Integration a product a cloud-based CRM platform - Blackcoffer Insights HomeOur Success StoriesIntegration a product a cloud-based CRM platformOur Success StoriesRetail & Supply ChainIntegration a product a cloud-based CRM platformByAjay Bidyarthy-September 15, 20222826Client BackgroundClient:A Leading Logistics Firm WorldwideIndustry Type:LogisticsServices:Import, Export, Supply Chain, Logistics, TradesOrganization Size:500+Project DescriptionThe main challenge faced team integration two systems themselves.Since one-by-one entering records module a mundane task a waste valuable time proposed automation using APIs.Our SolutionThe challenge divided two milestones sub-tasks each.1. First ingestion existing data cloud-based CRM platform.2. Second question automating process adding newer records cloud platform.Project DeliverablesThe client provided python scripting handling bulk data ingestion CRM also script handle daily synchronization data.Tools used– Python– MySQL Database– Postman– TeamViewerLanguage/techniques used– Automation– 3rdparty APIs– Authentication methods– Multi-Threading function calls– bat Scripts easier running scripts clientModels usedPython Frameworks like requests build custom client consumption APIs.Skills usedPython Programming, Mult-threading, APIsDatabases usedThe client provided a MySQL instance.Web Cloud Servers usedZohoWhat technical Challenges Faced Project Execution?– Writing client-side API-consumption code handling API calls Authentication Operations per task requirements.– Debugging API responses messy.How Technical Challenges Solved– Multiple alternatives discussed implemented python like conditional refreshing API tokens.– Automation daily synchronization handled use time deltas.– Logging operations efficiently handle errors future.Business Impact– Automated workflow client– need dull tasks like data entry CRM modules everything taken care using logic.URLhttps://www.exportgenius.in/Previous articleA web-based dashboard filtered data retrieval land recordsNext articleTransform API SDK library widgetAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSiOS Mobile Applications PortfolioJune 23, 2021How Will AI Make Decisions Tomorrow’s Wars?July 20, 2021Turning Professional Networking Data Actionable InsightsOctober 6, 2020Rise Internet Demand Impact Communications Alternatives...August 16, 2023Load moreRECOMMENDED INSIGHTSTraction Dashboards Marketing Campaigns PostsEnd-to-end tool predict Biofuel prices using IESO dataCar Detection Satellite ImagesGet Answers Structural Equation Modeling -------------------------------------------------------------------------------- /cleaned_articles/bctech2095.txt: -------------------------------------------------------------------------------- 1 | Title: Integration video-conferencing data existing web app - Blackcoffer Insights HomeOur Success StoriesIntegration video-conferencing data existing web appOur Success StoriesITIntegration video-conferencing data existing web appByAjay Bidyarthy-September 15, 20222733Client BackgroundClient:A Leading Tech Firm USAIndustry Type:IT & ConsultingServices:Software, Business Solutions, ConsultingOrganization Size:200+Project DescriptionIntegration 3rdparty APIs client’s platform.Client required meeting/conference data sites like gotomeeting/zoom.Our SolutionUsing APIs fetched data different platform rendered data client’s application.Modifed web application a UI handle form data accepting dates a timeframe – makes a request API handled server end returns meeting data required source.Project DeliverablesPushed code client’s github repository.Tools used– Python– PostmanLanguage/techniques used– Automation– 3rdparty APIs– Authenication methods– Multi-Threading function calls ( authentication api client )– UI component design get dates user-endModels usedPython Framework- Django , requestsSkills usedPython Programming, APIs , Multi-threading , Web DevelopementDatabases usedDefault project postgreSQLWeb Cloud Servers usedHerokuWhat technical Challenges Faced Project Execution– UI creation handling form data– Managing Validating form data process request server endHow Technical Challenges Solved– Created autmated functions views django handle requests made video-conferencing platform.– returns meeting data per user’s wish.Business Impact– Instead extracting meeting data adding usersany authorized user get meeting data wish.Project website urlhttps://www.codanalytics.net/Previous articleDesign & develop app retool shows progress added videoNext articleA web-based dashboard filtered data retrieval land recordsAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSPortfolio: Website, Dashboard, SaaS Applications, Web AppsJuly 13, 2022Management challenges future digitalization healthcare servicesDecember 2, 2020Real-Time sentiment analysis tool – Retail IndustryJuly 6, 2019Power BI Dashboard Operations, Transactions, Marketing Data, embedding the...May 14, 2022Load moreRECOMMENDED INSIGHTSMarketing Analytics Automate Leads Call Status ReportingAnalytics Healthcare IndustryHow forecast future technologies?Google Data Studio Pipeline GCP/MySQL -------------------------------------------------------------------------------- /cleaned_articles/bctech2096.txt: -------------------------------------------------------------------------------- 1 | Title: Design & develop app retool shows progress added video - Blackcoffer Insights HomeOur Success StoriesDesign & develop app retool shows progress of...BlackcofferOur Success StoriesITDesign & develop app retool shows progress added videoByAjay Bidyarthy-August 24, 20222566Client BackgroundClient:A Leading Tech Firm USAIndustry Type:IT & ConsultingServices:Software, Business Solutions, ConsultingOrganization Size:200+Project DescriptionThe objective develop a progress bar help costumes estimate analytics video.Our SolutionThe client wanted a progress bar following filters:Date filter: – Update progress bar count videos according date selectedCategory filter: – Update progress bar count videos according selected categoryWe created a SQL query getting a count videos full video table according filter selected appIn added video table columns missing solve created a SQL query joining added video table tables return count video according filter selectedProject DeliverablesApp retoolTools usedRetoolLanguage/techniques usedSQLSkills usedSQLDatabases usedSQL DatabaseWhat technical Challenges Faced Project ExecutionClient wanted date filter a video category filter data added video tableHow Technical Challenges SolvedWe join multiple data get category column date column applying filterProject SnapshotsProject VideoPrevious articleRise Electric Vehicles Impact Livelihood 2040Next articleIntegration video-conferencing data existing web appAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSHow Setup Custom Domain Google App Engine Application?February 13, 2021What Analytics & Outsourcing engagement model right you?August 2, 2018Deploy node.js apps google app engine, google cloud platformMay 16, 2021Transforming Insurance Claim Processing Automation & Artificial IntelligenceApril 25, 2019Load moreRECOMMENDED INSIGHTSSupplier Insights Decision Supports eCommerce OutletsBig Data Analytics IoT Oil Gas IndustryThe future InvestingHow marketers start integrating AI work -------------------------------------------------------------------------------- /cleaned_articles/bctech2100.txt: -------------------------------------------------------------------------------- 1 | Title: app updating email id user stripe refund tool using retool - Blackcoffer Insights HomeOur Success StoriesAn app updating email id user stripe...Our Success StoriesHealthcareAn app updating email id user stripe refund tool using retoolByAjay Bidyarthy-July 8, 20222811Client BackgroundClient:A Leading Healthcare Tech Firm USAIndustry Type:HealthcareServices:Healthcare SolutionsOrganization Size:200+Project DescriptionThe client needed two apps retoolUpdate email id customerStripe refund app two options full payment partial paymentOur SolutionWe create following two apps retoolTakes old email id user new email id user update email id clicked old email id updated new email id. updating email id used stripe APIThe user select email id user payment id user table user get two options a refundFull payment: – option refunds whole amount customerPartial payment: – option refunds partial amount entered userProject DeliverablesApps retoolTools usedRetoolStripeLanguage/techniques usedJavaScriptModels usedWe used modelsSkills usedAPIDatabases usedStripe databaseWhat technical Challenges Faced Project ExecutionThe main challenge creating a full payment option using stripe API. customer already received a partial amount performing a full refund refund amount always greater balance amountHow Technical Challenges SolvedTo solve full payment option issue, calculate balance amount provided amount full payment event retoolBusiness ImpactUsing apps it’s easy client update email id customer refund customers client refund two option full payment partial paymentProject SnapshotsProject website urlPrevious articleAn AI ML-based web application detects correctness text a given videoNext articleWeb Data ConnectorAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSPPT: Solution quadratic assignment problems (QAP) using Ant Colony SystemFebruary 18, 2019Descriptive vs Inquisitive vs Predictive AnalyticsApril 4, 2019Dashboard track analytics website using Google Analytics...July 1, 2022Artificial intelligence business: Separating real hypeSeptember 25, 2018Load moreRECOMMENDED INSIGHTSThe Metaverse Implications Digital Future.Travel Tourism OutlookCoronavirus: Effect Hospitality IndustryWhy scams like Nirav Modi Happen Indian banks? -------------------------------------------------------------------------------- /cleaned_articles/bctech2101.txt: -------------------------------------------------------------------------------- 1 | Title: AI ML-based web application detects correctness text a given video - Blackcoffer Insights HomeOur Success StoriesAn AI ML-based web application detects correctness text in...Our Success StoriesITLifestyle, eCommerce & Online Market PlaceAn AI ML-based web application detects correctness text a given videoByAjay Bidyarthy-July 8, 20222952Client BackgroundClient:A Design & Media firm USAIndustry Type:MarketingServices:Consulting, Software, Marketing SolutionsOrganization Size:100+Project ObjectiveCreate a python web application detects text checks spelling written text videos prints count wrong spelling endProject DescriptionDeveloping a dockerized Django web application detecting text checking spelling written text video printing count wrong spelling end deploying application google cloudOur SolutionWe created a python web application Django framework user uploads video application run keras-ocr model frame video keep count wrong words end provides video bounding box around words. correct words creates green bounding box wrong words creates red bounding box also provides summation count wrong words.Project DeliverablesDeployed dockerized web application google cloud generate video bounding box around textsTools usedDockerRedis ServerDjangoCeleryNginxOpencvNLTKMoviepyLanguage/techniques usedPythonHtmlCSSJavaScriptModels usedWe used keras-ocr model detecting text form video creating bounding box around wordsSkills usedNatural language processing,Machine learning,Image processing,Web development,Python programmingDatabases usedDjango Sqlite3,Redis ServerWeb Cloud Servers usedGoogle cloudWhat technical Challenges Faced Project ExecutionRunning model frame videoShow progress bar progress workHow Technical Challenges SolvedFor running model frame video used celery runs model backend applicationWe used celery backend progressrecorder updated every time model detected text frame videoProject SnapshotsProject website urlhttp://34.68.134.64/Previous articleWebsite Tracking Insights using Google Analytics, & Google Tag ManagerNext articleAn app updating email id user stripe refund tool using retoolAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSAudify Music Player Website MERN StackMarch 14, 2021How Login Logout Time Tracking Employees Office done...September 28, 2021Get Answers Structural Equation ModelingApril 12, 2019Rising Cities Impact Economy, Environment, Infrastructure,...August 18, 2023Load moreRECOMMENDED INSIGHTSWill ever understand nature consciousness?Car Parking Management SystemMarketing Drives Results A Focus ProblemsLessons past: key learnings relevant coronavirus... -------------------------------------------------------------------------------- /cleaned_articles/bctech2104.txt: -------------------------------------------------------------------------------- 1 | Title: Power BI Dashboard Operations, Transactions, Marketing, Anaytics HomeOur Success StoriesPower BI Dashboard Operations, Transactions, Marketing Data, embedding Dashboard...Our Success StoriesITPower BI Dashboard Operations, Transactions, Marketing Data, embedding Dashboard Web AppByAjay Bidyarthy-May 14, 20223120Client BackgroundClient:A leading tech firm USAIndustry Type:IT ServicesServices:Consulting, Software, Marketing SolutionsOrganization Size:100+Project ObjectiveCreate a dashboard Assets Performance react App. users evaluate Key metrics data analytics forecasting.Project DescriptionThe client requires two pages:Screening Asset PerformancePortfolio Investingaccording criteria sector-based.Our SolutionBy using Power BI achieve requirement without additional stack. requires a subscription enhance report.Using Page Navigation bookmarks create reports like Web Application React App.Project DeliverablesAsset Report PageInvestor PageTools usedPower BIAzure AADMongo DB BI ConnectorODBC ConnectorDAX StudioLanguage/techniques usedSTAR SCHEMASkills usedDATA MODELLING.Performance Analyser.Vertipaq Analyser.Databases usedMongo DBWeb Cloud Servers usedAZUREWhat technical Challenges Faced Project ExecutionTime loading pages increased due raw data.Cold start Report taking time usualHow Technical Challenges SolvedFrom Snowflake Star Schema achieved performance ReportBy using Performance Analyser debugging resolved many glitches happening.Extraction, Transformation makes data less complex removing unwanted data a website perspective makes data shrink achieved 75% Data Reduction.Business ImpactLess coding Power BI speeds development process achieves Best UX less time.Project SnapshotsProject website urlhttps://digital.bctriangle.comProject VideoPrevious articleNFT Data Automation (looksrare), ETL toolNext articleDashboard track analytics website using Google Analytics Google Tag ManagerAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSImpact COVID-19 Engineering Medical College pandemic...December 7, 2021Get Answers Structural Equation ModelingApril 12, 2019Efficient AWS Infrastructure Setup Management: Addressing Security, Scalability, ComplianceMarch 16, 2024AI Solutions Foreign Exchange – Automated Algo Trading ToolJuly 24, 2023Load moreRECOMMENDED INSIGHTSPower BI integration RestAPI, SAML IntegrationBenefits Big Data Different fieldsImpact COVID-19 Engineering Medical College pandemic...PPT: Solution quadratic assignment problems (QAP) using Ant Colony System -------------------------------------------------------------------------------- /cleaned_articles/bctech2106.txt: -------------------------------------------------------------------------------- 1 | Title: Optimize data scraper program easily accommodate large files solve OOM errors - Blackcoffer Insights HomeOur Success StoriesOptimize data scraper program easily accommodate large files solve...Our Success StoriesITOptimize data scraper program easily accommodate large files solve OOM errorsByAjay Bidyarthy-May 13, 20222661Client BackgroundClient:A leading tech firm IndiaIndustry Type:IT ServicesServices:SAAS services, Marketing services, Business consultantOrganization Size:100+Project DescriptionBuilding a large data warehouse houses projects tenders data world collected official government websites, multilateral banks, state local government agencies, data aggregating websites, etc.Our SolutionWe tried multiple solutions prevent program running memory. used python pandas techniques control use memory worked files work others. Provided solutions using vaex ,dask module datatables.Project DeliverablesDesired changes code committing github.Tools usedVscodePythonGithubSlackLanguage/techniques usedChunkingdask Dataframevaexdatatablepython.Skills usedCloudPythonTime complexityWhat technical Challenges Faced Project ExecutionSystem specs requirement main issue project RAM available less got used quickly.How Technical Challenges SolvedTeam viewer use remote desktop higher specs would sufficient enough solve problem.Business ImpactProvided various techniques solve memory issues.Suggested parallel programming decrease execution time 12% making getting tender data a much faster rate.Project SnapshotsProject website urlhttps://github.com/Taiyo-ai/opentenders-euhttps://opentender.euPrevious articleMaking a robust way sync data airtables mongoDB using python – ETL SolutionNext articleNFT Data Automation (looksrare), ETL toolAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSHow Login Logout Time Tracking Employees Office done...September 28, 2021Transforming Healthcare SystemsApril 17, 2021AI healthcare Improve Patient OutcomesJune 26, 2021Code Review ChecklistApril 10, 2020Load moreRECOMMENDED INSIGHTSElectric Vehicles (EV) Load Management System Forecast Energy DemandAI ML-Based YouTube Analytics Content Creation Tool Optimizing...How Metaverse will change life?Data Transformation -------------------------------------------------------------------------------- /cleaned_articles/bctech2108.txt: -------------------------------------------------------------------------------- 1 | Title: Incident Duration Prediction - Infrastructure Real Estate - Blackcoffer Insights HomeOur Success StoriesIncident Duration Prediction – Infrastructure Real EstateOur Success StoriesInfrastructure & Real EstateResearch & AcademiaIncident Duration Prediction – Infrastructure Real EstateByAjay Bidyarthy-February 27, 20222703Client BackgroundClient:A leading research institution middle eastIndustry Type:ResearchServices:R&DOrganization Size:1000+Project ObjectiveTo complete a Research Paper draft training various Machine Learning models predict Incident Duration based various parameters given dataset summarising results.Project DescriptionGiven a set researches, need analyse compare various machine learning deep learning models predict Incident Duration given dataset. dataset contained Short durations well Long durations. Build models set durations, compare get best all.Our SolutionHere, predict traffic incident duration machine learning tools techniques i.e. XGBoost, SVR Deep Learning algorithm using tensor flow. First two models run Python Interpreter whereas Deep learning model run R studio, three dataset compared models based MAE (mean absolute error). Initially, done a preliminary analysis collected incident duration data, collect statistical characteristics variables used research.Project DeliverablesPython Script model.Documentation Research Work.Tools usedPython InterpreterLanguage/techniques usedLanguage Used: PythonLibraries Used: pandas, sklearn, numpy, keras, pickleModels usedXGBRegressorSVRSGDRegressorSequentialDecisionTreeRegressorSkills usedProgramming, Statistical AnalysisProject SnapshotsPrevious articleStatistical Data Analysis Reinforced ConcreteNext articleHow Metaverse work Financial sector?Ajay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSPowerBI REST API – Fetching Dataflow Refresh Schedules semantic...August 25, 2024Coronavirus Disease (COVID-19) Effect: Impact Role Mass Media...March 30, 2020KPI Dashboard AccountantsJuly 21, 2023Impact COVID-19 pandemic public transportation industries.June 23, 2020Load moreRECOMMENDED INSIGHTSEquity Waterfalls Model-Based SaaS Application Real Estate SectorAI Dashboard Health Fitness – In-Depth LookSteps Meta-AnalysisTurn Website Analytics Actionable Insights & Decisions Using Neo4J... -------------------------------------------------------------------------------- /cleaned_articles/bctech2110.txt: -------------------------------------------------------------------------------- 1 | Title: Database Normalization & Segmentation Google Data Studio Dashboard Insights - Blackcoffer Insights HomeOur Success StoriesDatabase Normalization & Segmentation Google Data Studio Dashboard InsightsOur Success StoriesITDatabase Normalization & Segmentation Google Data Studio Dashboard InsightsByAjay Bidyarthy-February 27, 20222817Client BackgroundClient:A leading marketing firm USAIndustry Type:Market ResearchServices:Marketing, ConsultancyOrganization Size:60+Project ObjectiveTo combine different datasets.To make dashboards every dataset individually.Project DescriptionPhase – 1: project first combine different datasets individually make single file source.Phase – 2: Make Good looking reports file individually.Our SolutionWe used pandas dataframe combine different files make single file source. used Google Data Studio make good looking better reports good UI.Project DeliverablesWe provided a Google Data Studio report file deliverable project.Tools usedPython, Google Data Studio, Google ChromeLanguage/techniques usedPython Programming SQL queries editor.Models usedSDLC model used project. used SDLC model analysis, design, implementation, testing maintenance.Skills usedData cleaning, Data Pre-processing, Data Visualisation used project.Databases usedWe used traditional file systems database storage.What technical Challenges Faced Project ExecutionCombining Data sets single file.Making good looking UI dashboards.How Technical Challenges SolvedI used pandas dataframe combine different datasets made a single file every individual source. I used Google Data Studio make dashboard project.Project SnapshotsProject VideoPrevious articlePower BI dashboard drive insights complex data generate business insightsNext articleStatistical Data Analysis Reinforced ConcreteAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSMarketing Drives Results A Focus ProblemsNovember 25, 2019Design & develop app retool shows progress...August 24, 2022Behavior Based Chi-Square model Detect Data-Exfiltration NetworkMay 15, 2017Rise Internet Demand Impact Communications Alternatives...August 17, 2023Load moreRECOMMENDED INSIGHTSAn outlook healthcare year 2040, it...Estimating impact COVID-19 world workData TransformationPharmaceutical Data Power BI Report -------------------------------------------------------------------------------- /cleaned_articles/bctech2111.txt: -------------------------------------------------------------------------------- 1 | Title: Power BI dashboard drive insights complex data generate business insights - Blackcoffer Insights HomeOur Success StoriesPower BI dashboard drive insights complex data generate business...Our Success StoriesITPower BI dashboard drive insights complex data generate business insightsByAjay Bidyarthy-February 26, 20223064Client BackgroundClient:A leading marketing firm USAIndustry Type:Market ResearchServices:Marketing, ConsultancyOrganization Size:100+Project DescriptionPhase – 1: project first made heatmap two columns named Author Data Source. two combining two tables named NY_data nodeid_views made report data.Phase – 2: Success story given pageviews 35000, pageviews lies 3500-35000 story labelled needs improvement 3500 story labelled failure.Phase – 3: powerbi report made find different insights data like different tables drawn different attributes data like pie chart, time series chart, comparison charts. data updated every week report generated automatically.Our SolutionWe provided Phase 1 powerbi sql editor combining two tables using sql queries. phase 2 used power bi program tool written a script Python calculate success story. Phase 3 used internal features Power BI find insights data.Project DeliverablesWe provided a PowerBI report file deliverable project.Tools usedPython, PowerBI, Google ChromeLanguage/techniques usedPython Programming SQL queries editor.Models usedWaterfall model used project.Skills usedData cleaning, Data Pre-processing, Data Visualisation used project.Databases usedWe used traditional file systems database storage.What technical Challenges Faced Project ExecutionDrawing heatmap PowerBI.Combining two tables basis pageviews.Converting time series data 5 minute format.How Technical Challenges SolvedWe installed a new add PowerBI draw heatmap project used SQL editor combine tables basis page views. used python programming convert time series data 5 minute time gap format.Project SnapshotsProject VideoPrevious articleReal-time dashboard monitor infrastructure activity MachinesNext articleDatabase Normalization & Segmentation Google Data Studio Dashboard InsightsAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSSentiment Analysis Bot Price PredictionMarch 10, 2021Creating a custom report dashboard using data got from...January 16, 2022Medical ClassificationSeptember 16, 2022Why a severe immunological inflammatory explosion those...March 30, 2020Load moreRECOMMENDED INSIGHTSHow artificial intelligence boost productivity level?Pharmaceutical Data Power BI ReportStudent Database Management SystemData Analytics Optimization Solution Enhancing Renewable Energy Efficiency -------------------------------------------------------------------------------- /cleaned_articles/bctech2112.txt: -------------------------------------------------------------------------------- 1 | Title: Real-time dashboard monitor infrastructure activity Machines - Blackcoffer Insights HomeOur Success StoriesReal-time dashboard monitor infrastructure activity MachinesOur Success StoriesInfrastructure & Real EstateITReal-time dashboard monitor infrastructure activity MachinesByAjay Bidyarthy-February 26, 20223149Client BackgroundClient:A leading tech firm EuropeIndustry Type:ITServices:Software ServicesOrganization Size:30+Project ObjectiveFor current project, hope develop a real-time dashboard (* updates every several minutes). Currently, multiple Ubuntu machines sending messages every minute Apache Pulsar.Project DescriptionDeveloping a realtime updating dashboard display metadata various machines a server pandio queue.The dahboard must display count “inactive” , “active” “down” servers a table displaying details machines different color scheme type server/machine.Our SolutionWe used Django framework develop dashboard didn’t require ec2 instance active machine problem using streamlit.For communication webpage fetched data used django channel .We used django background task module make fetching run forever background.Project DeliverablesReal time updating Dashboard separate color scheme different types machines.Storing historical data sqlite3 db.Tools usedDjangoWeb ChannelsD3 jsReddis serverSkills usedPythonDjango FrameworkDjango web channelsHTML/CSS + JSDatabases usedDjango sqlite3 database.Web Cloud Servers usedAWSWhat technical Challenges Faced Project ExecutionMaking dashboard run forever using streamlitData updation realtime using django channelsHow Technical Challenges SolvedSwitched entire dashboard django frameworkWe redirected data channels local reddis server.Project SnapshotsProject website urlDevelopment hosted URLPrevious articleElectric Vehicles (EV) Load Management System Forecast Energy DemandNext articlePower BI dashboard drive insights complex data generate business insightsAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSReplacing existing pavement roads, parking lots sidewalks pavement made...July 17, 2019Data Driven Dashboards, Foundation Application IndustryMay 26, 2017Sentiment Analysis Bot Price PredictionMarch 10, 2021SurveyMonkey Business Questioner Report using Power BIJune 26, 2021Load moreRECOMMENDED INSIGHTSAn outlook healthcare year 2040, it...React Native Apps Development PortfolioAdvanced AI Thermal Person DetectionFuture Work: AI Entered Workplace -------------------------------------------------------------------------------- /cleaned_articles/bctech2114.txt: -------------------------------------------------------------------------------- 1 | Title: Power BI Data-Driven Map Dashboard - Blackcoffer Insights HomeOur Success StoriesPower BI Data-Driven Map DashboardOur Success StoriesITPower BI Data-Driven Map DashboardByAjay Bidyarthy-February 26, 20223210Client BackgroundClient:A leading marketing firm USAIndustry Type:Market ResearchServices:Marketing, ConsultancyOrganization Size:60+Project ObjectiveChange bubble colors dynamically.Make table charts linked. a user clicks tables values, bubble chart map highlighted relates table.Project Description“I a map visual. I would like dynamically change colours bubbles.”The report page several filters KPI Dashboard, whose metrics change dynamically user clicks a certain element. Similarly map also change dynamically relative filter.Our SolutionAdded website data Details table map visualization, makes bubbles get coloured dynamically according requirement websites data.Project DeliverablesThe Power BI ( .pbix ) file updated solutionTools usedPower BISkills usedPower BIData VisualizationData AnalysisDatabases usedThe database came Power BI file received clientWhat technical Challenges Faced Project ExecutionThe map linkedMap Bubbles dynamicHow Technical Challenges SolvedRefactoring data model using appropriate keys link data togetherThat made Map change according Slicers/FiltersTo Change colour, Bookmark buttons used dashboard bring dynamic colour changing slicing (works published)Project SnapshotsProject VideoPrevious articleAI Conversational Bot using RASANext articleElectric Vehicles (EV) Load Management System Forecast Energy DemandAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSLessons past: key learnings relevant coronavirus...May 1, 2020Internet Demand’s Evolution, Communication Impact, 2035’s Alternative PathwaysAugust 18, 2023Management challenges future digitalization healthcare servicesDecember 2, 2020Interpret Coefficients Regression ModelsApril 4, 2019Load moreRECOMMENDED INSIGHTSHow prepared India tackle a possible COVID-19 outbreak?Coronavirus: Effect Hospitality IndustryTransforming Healthcare SystemsHow Login Logout Time Tracking Employees Office done... -------------------------------------------------------------------------------- /cleaned_articles/bctech2117.txt: -------------------------------------------------------------------------------- 1 | Title: MetaBridges API Decentraland Integration - AR, VR - Blackcoffer Insights HomeOur Success StoriesMetaBridges API Decentraland Integration – AR, VROur Success StoriesInfrastructure & Real EstateITMetaBridges API Decentraland Integration – AR, VRByAjay Bidyarthy-January 24, 20223282Client BackgroundClient:A leading tech firm USAIndustry Type:ITServices:Consulting, Software, Blockchain, MetaverseOrganization Size:20+Project ObjectiveTo integrate Metaverse environments help EC2, S3 bucket Decentraland SDK.Project DescriptionMove 3D model files EC2 instance S3 bucked using aws-sdk.Our SolutionConfigure s3 bucket aws account, create user s3 bucket api keys, andapi secret. Put api key, aapi secret, bucket name bucket region inenvironment variable use app. Install aws-sdk implement s3 bucket.Create a function send file nodejs server s3 bucket.Project DeliverablesAws ec2 instance credentials, s3 bucket credentials. Code used projectTools usedvs code editor, git bash terminal, google chrome web browser. Metamask wallet, cryptocurrency, blockchain, bitcoin, metamask, metaverse, VR, AR, Virtual Reality, Augmented RealityLanguage/techniques usedJavascript language used. Metamask wallet, cryptocurrency, blockchain, bitcoin, metamask, metaverse, VR, AR, Virtual Reality, Augmented RealityModels useddcl SDK (Decentraland sdk nodejs), aws-sdk, awscli.Skills usedNode js project setup, Dcl sdk setup, Aws ec2 instance setup aws cli,S3 bucket connection aws-sdk. cryptocurrency, blockchain, bitcoin, metamask, metaverse, VR, AR, Virtual Reality, Augmented RealityDatabases usedNo database usedWeb Cloud Servers usedAWS cloud server usedWhat technical Challenges Faced Project ExecutionMaking application port ec2 instance available globaly.How Technical Challenges SolvedSearch blogs videos solution. make done change inSecurity group ec2 instance.Business ImpactAs Decentraland a platform based NFT main part business related NFT cryptocurrency.Project SnapshotsProject VideoPrevious articleMicrosoft Azure chatbot LUIS (Language Understanding)Next articleAWS Lex Voice ChatbotAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSSolution quadratic assignment problems (QAP) using Ant Colony SystemFebruary 18, 2019A Leading Firm USA, Website SEO & OptimizationSeptember 5, 2021Database Discovery Tool using OpenAIJanuary 20, 2024The Emergence Data AnalyticsJanuary 11, 2019Load moreRECOMMENDED INSIGHTSNew Jersey Based Micro Business Sentiment AnalysisElectric Vehicles (EV) Load Management System Forecast Energy DemandIs telehealth future healthcare?Automated Campaign Management System: A Comprehensive Solution LinkedIn Email... -------------------------------------------------------------------------------- /cleaned_articles/bctech2118.txt: -------------------------------------------------------------------------------- 1 | Title: Microsoft Azure chatbot LUIS (Language Understanding) - Blackcoffer Insights HomeOur Success StoriesMicrosoft Azure chatbot LUIS (Language Understanding)Our Success StoriesLifestyle, eCommerce & Online Market PlaceMicrosoft Azure chatbot LUIS (Language Understanding)ByAjay Bidyarthy-January 24, 20222988Client BackgroundClient:A leading retail firm USAIndustry Type:RetailServices:e-commerce, retail businessOrganization Size:100+Project ObjectiveTo create advanced chatbot using Microsoft Azure cognitive service take orders customer behalf a pizza restaurant give order summary end result user.Project DescriptionThe project uses MS Azure LUIS service language understanding receive order details a customer provide order summary. Also display various menu options customer a dynamic method.Our SolutionOur solution create a chatbot MS Azure platform using LUIS service bot-framework composer environment. Use dynamic hero cards display menu user get a better experience.Project DeliverablesChatbotTools usedBot Framework composerBot emulatorMS Azure LUIS servicesLanguage/techniques usedBot framework composerNatural language processingModels usedMS Azure LUISMS Azure QnAMS Azure speed SDKSkills usedDeep learningWeb developmentCloud techWeb Cloud Servers usedMicrosoft Azure web platformWhat technical Challenges Faced Project ExecutionMonthly quota LUIS authoring service reachedTracking multiple items ordered userAccessing relevant images menu itemHow Technical Challenges SolvedSwitching a suitable pricing tier would eventually switch move onto production phaseCreating custom functions intents different trackersUsing open license images internetProject SnapshotsProject website urlDemoPrevious articleDo Social Media Owned Meta?Next articleMetaBridges API Decentraland Integration – AR, VRAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSBank Risk Management IndiaJune 1, 2019Advanced AI Thermal Person DetectionJuly 22, 2023Blockchain FintechSeptember 14, 2019Digital Strategic Foresight Platform – Smart AI-Driven DashboardFebruary 22, 2019Load moreRECOMMENDED INSIGHTSEmbedding care robots society practice: Socio-technical considerationsWill Machine Replace Human Future Work?How artificial intelligence affect environmentGrafana Dashboard visualize analyze sensors’ data -------------------------------------------------------------------------------- /cleaned_articles/bctech2119.txt: -------------------------------------------------------------------------------- 1 | Title: Impact news, media, press innovation, startups, investments - Blackcoffer Insights HomeOur Success StoriesImpact news, media, press innovation, startups, investmentsOur Success StoriesResearch & AcademiaImpact news, media, press innovation, startups, investmentsByAjay Bidyarthy-January 16, 20222755Client BackgroundClient:A leading research institution wordIndustry Type:Research, R&DServices:R&DOrganization Size:1000+Project ObjectiveMake data ready predictive modelling.Making Google Data Studio dashboard.Project DescriptionPhase – 1: project first clean data data noisy, filter needed columns data.Phase – 2: Finding co-relation pitchbook data output files.Phase – 3: Making dashboard Google Data Studio project.Our SolutionWe used pandas numpy clean data make useful used predictive modelling. found co-relation tempa msa pitchbook data output files like textual file, ai_ml_tm file etc. made dashboard using Google Data Studio.Project DeliverablesWe provided a excel file consisting clean data Google Data Studio report.Tools usedPython, Google Data Studio, Google ChromeLanguage/techniques usedPython ProgrammingModels usedWaterfall model used project.Skills usedData cleaning, Data Pre-processing, Data Visualisation used project.Databases usedWe used traditional file systems database storage.What technical Challenges Faced Project ExecutionCleaning data major challenge faced executing project. data a lot noise. difficult find data useful data useful project. Secondly co relation output files pitchbook data. nothing common datasets. difficult find co-relation them.How Technical Challenges SolvedWe used pandas dataframe clean data make ready predictive modelling used Google Data studio find insights different datasets.Project SnapshotsProject VideoPrevious articleAWS QuickSight Reporting DashboardNext articleHow Metaverse Shaping Future?Ajay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSHow Overcome Fear Making MistakesAugust 23, 2020Automated Orthopedic Case Report Generation: Harnessing Web Scraping AI IntegrationMarch 16, 2024Amazon Buy Bot, Automation AI tool Auto-CheckoutsJune 26, 2021Networking Platform – a lookMarch 14, 2021Load moreRECOMMENDED INSIGHTSMisesBot Activate – Markov Chain, Text GeneratorHow Data Analytics AI used halt COVID-19...Rise Cybercrime Effect Year 2040.How robots help e-learning platforms? -------------------------------------------------------------------------------- /cleaned_articles/bctech2124.txt: -------------------------------------------------------------------------------- 1 | Title: Creating a custom report dashboard using data got Atera API - Blackcoffer Insights HomeOur Success StoriesCreating a custom report dashboard using data got Atera...Our Success StoriesITCreating a custom report dashboard using data got Atera APIByAjay Bidyarthy-January 16, 20223084Client BackgroundClient:A leading Marketing firm USAIndustry Type:MarketingServices:Marketing, consulting, ads, business solutionsOrganization Size:20+Project DescriptionAtera.com used RMM, agent every machine. tracks a machine goes down, initial response time etc.., website doesn’t provide standard reports, needed create a custom report.Our SolutionImporting data Atera API JupyterUsing Web Scraping download JSON dataConvert JSON data Data Frame download PC.Clean data required columnsUpload data google sheets.Connect google sheets google data studioCreate dashboard dataTools usedPython (Pandas, requests)Google SheetsGoogle Data StudioSkills usedAnalyticsProgramming LanguageDatabases usedContacts.csvCustomers.csvTickets.csvAlerts.csvWhat technical Challenges Faced Project Execution?I found difficult downloading data.How Technical Challenges SolvedOnce I figured I using wrong Authorization key login I able solve issue, convert curl command pythonProject SnapshotsProject website urlhttps://datastudio.google.com/reporting/5e61aecb-a420-41cc-afba-d0ca37f69132Project VideoPrevious articleAzure Data Lake Power BI DashboardNext articleBig Data solution online multivendor marketplace eCommerce businessAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSMicrosoft Azure chatbot LUIS (Language Understanding)January 24, 2022AI Chatbot using LLM, Langchain, LLamaJuly 7, 2024Interpret Coefficients Regression ModelsApril 4, 2019Python model analysis sector-specific stock ETFs investment...December 31, 2022Load moreRECOMMENDED INSIGHTSHow Metaverse Shaping Future?Optimize data scraper program easily accommodate large files and...Datawarehouse, Recommendations Engine AirBNBData ETL: Local Service Ads Leads BigQuery -------------------------------------------------------------------------------- /cleaned_articles/bctech2129.txt: -------------------------------------------------------------------------------- 1 | Title: React Native Apps Development Portfolio - Blackcoffer Insights HomeOur Success StoriesReact Native Apps Development PortfolioOur Success StoriesITReact Native Apps Development PortfolioByAjay Bidyarthy-September 6, 20214106Here list react native apps developed team resources:https://itunes.apple.com/us/app/truckmap-truck-gps-routes/id1198422047?mt=8https://play.google.com/store/apps/details?id=com.truckmap.truckmaphttps://play.google.com/store/apps/details?id=com.verifai.standalonehttps://apps.apple.com/nl/app/verifai/id1504214033https://apps.apple.com/de/app/meetlist-lokale-aktivit%C3%A4ten/id1439183715https://play.google.com/store/apps/details?id=de.mlug.meetlisthttps://play.google.com/store/apps/details?id=com.payroo.employeehttps://play.google.com/store/apps/details?id=com.vahcarehttps://play.google.com/store/apps/details?id=com.candorivfPrevious articleA Leading Law Firm USA, Website SEO & OptimizationNext articleMarketing, sales, financial data business dashboard (Wink Report)Ajay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSIntegration Python Power BI, Python External Tool...June 26, 2021Do Ethnic differences possibly influence risk Multiple Sclerosis development...June 4, 2019Advanced AI Pedestrian Crossing SafetyJuly 22, 2023Centrality Measures & Meaning Network GraphsApril 2, 2021Load moreRECOMMENDED INSIGHTSCloud-Based Data Modeling Analysis Platform Drag-and-Drop Interface OpenAI...Data Integration MarketersAI Dashboard Health Fitness – In-Depth LookIoT & AI/ML Solution Gas Stations -------------------------------------------------------------------------------- /cleaned_articles/bctech2130.txt: -------------------------------------------------------------------------------- 1 | Title: A Leading Law Firm USA, Website SEO & Optimization - Blackcoffer Insights HomeOur Success StoriesA Leading Law Firm USA, Website SEO & OptimizationOur Success StoriesITA Leading Law Firm USA, Website SEO & OptimizationByAjay Bidyarthy-September 5, 20213276Client BackgroundClient:A leading marketing firm USAIndustry Type:MarketingServices:Marketing consultingOrganization Size:100+Project ObjectiveConnect website Search Console, Google Analytics Facebook Pixel Google Tag Manager.Fix SEO website.Project DescriptionConnecting website Google Search Console, Google Analytics Facebook Pixel Google Tag Manager.Fixing SEO website.Our SolutionWebsite connected Google Search Console, Google Analytics Facebook Pixel successfully.Fixed themeta description errorbroken link error404 error, etc.Tools usedSquarespaceGoogle Tag ManagerGoogle AnalyticsGoogle Search ConsoleLanguage/techniques usedJavaScriptSkills usedSquarespaceGoogle Tag ManagerGoogle AnalyticsGoogle Search ConsoleJavaScriptProject SnapshotsProject website URLhttps://www.keepingorlandomoving.com/Previous articleA Leading Hospitality Firm USA, Website SEO & OptimizationNext articleReact Native Apps Development PortfolioAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSIMPACT COVID-19 GLOBAL ECONOMYApril 13, 2020How overcome fear making mistakes?August 20, 2020Impact coronavirus Indian economyApril 15, 2020Transforming Managing a Large-Scale SQL Pedigree Database Neo4j Graph...August 25, 2024Load moreRECOMMENDED INSIGHTSCOVID-19: countries responding?COVID-19 Impact Hospitality IndustryHow will COVID-19 affect world work?E-commerce Store Analysis – Purchase Behavior, Ad Spend, Conversion, Traffic, etc… -------------------------------------------------------------------------------- /cleaned_articles/bctech2131.txt: -------------------------------------------------------------------------------- 1 | Title: A Leading Hospitality Firm USA, Website SEO & Optimization - Blackcoffer Insights HomeOur Success StoriesA Leading Hospitality Firm USA, Website SEO & OptimizationOur Success StoriesITA Leading Hospitality Firm USA, Website SEO & OptimizationByAjay Bidyarthy-September 5, 20213262Client BackgroundClient:A leading marketing firm USAIndustry Type:MarketingServices:Marketing consultingOrganization Size:100+Project ObjectiveWorking On-page SEO pages make user-friendly feasible crawlers make site indexing better.Project DescriptionFirstly, exploring Liverez a new platform then, performing intermediate SEO like page titles description, completing word count, alt. text removing duplicate page title description.Our SolutionTo increase organic traffic site improve insights.Project DeliverablesThere a bit improvement traffic site.Tools usedBrightlocal.com, Yoast SEO, GrammarlyLanguage/techniques usedBasic HTMLSkills usedON-page SEOProject SnapshotsProject website urlhttps://www.missionbeach.com/Previous articleA Leading Firm USA, Website SEO & OptimizationNext articleA Leading Law Firm USA, Website SEO & OptimizationAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSMethodology ETL Discovery Tool using LLMA, OpenAI, LangchainFebruary 27, 2024iOS Mobile Applications PortfolioJune 23, 2021Automated Job Data Import Management Solution Enhanced EfficiencyAugust 25, 2024Add SPF Record, Cpanel, BigrockAugust 17, 2019Load moreRECOMMENDED INSIGHTSBuilding Analytics Dashboard a PDF Parsing Pipeline Data...Time Series Analysis Trend Forecasting Solution Predicting News TrendsUsing Graph Technology Create Single Customer View.iOS Mobile Applications Portfolio -------------------------------------------------------------------------------- /cleaned_articles/bctech2132.txt: -------------------------------------------------------------------------------- 1 | Title: A Leading Firm USA, Website SEO & Optimization - Blackcoffer Insights HomeOur Success StoriesA Leading Firm USA, Website SEO & OptimizationOur Success StoriesITA Leading Firm USA, Website SEO & OptimizationByAjay Bidyarthy-September 5, 20213062Client BackgroundClient:A leading marketing firm USAIndustry Type:MarketingServices:Marketing consultingOrganization Size:100+Project ObjectiveFixing On-Page SEO websiteProject DescriptionFixing On-Page SEO contains things like title, meta description, image-alt text, broken links, 404 error page, multiple h1 tag one page, duplicate title/description, dynamic URL, sparse content page (word count <500), etc.Our SolutionFixed possible solutions improving SEO health score.Fixed, image-alt text error, title, meta description, broken links, dynamic URL, 404 error page, sparse content pages, contact information pages, connecting website Google search console.Tools usedAhrefsWordPressGoogle Search ConsoleLanguage/techniques usedHTMLRedirection pluginSkills usedHTMLWordPressGoogle Search ConsoleProject SnapshotsProject website URLURLhttps://www.jupiteroutdoorcenter.com/HomePrevious articleA Leading Musical Instrumental, Website SEO & OptimizationNext articleA Leading Hospitality Firm USA, Website SEO & OptimizationAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSHow COVID-19 crisis redefining jobs services?August 15, 2020Oil prices year 2040, will impact...August 20, 2022AI healthcare Improve Patient OutcomesJune 26, 2021An outlook healthcare year 2040, it...August 20, 2022Load moreRECOMMENDED INSIGHTSAirbnb & Homeaway Pricing RecommendationImpress a Modern WebsiteData TransformationAnalytics Healthcare Industry -------------------------------------------------------------------------------- /cleaned_articles/bctech2133.txt: -------------------------------------------------------------------------------- 1 | Title: A Leading Musical Instrumental, Website SEO & Optimization - Blackcoffer Insights HomeOur Success StoriesA Leading Musical Instrumental, Website SEO & OptimizationOur Success StoriesITProduction & ManufacturingA Leading Musical Instrumental, Website SEO & OptimizationByAjay Bidyarthy-September 5, 20212994Client BackgroundClient:A leading marketing firm USAIndustry Type:MarketingServices:Marketing consultingOrganization Size:100+Project ObjectiveConnect website Google Tag Manager.Remove error.Project DescriptionRemove previously added code add new code connecting Google Tag Manager.Remove 5xx error website.Our SolutionWebsite connected Google Tag Manager successfully.Removed 5xx error.Tools usedGoogle Tag ManagerWordPressLanguage/techniques usedJavaScriptSkills usedWordPressGoogle Tag ManagerProject website URLURL:https://www.hamiltonpianoco.com/Previous articleA Leading Firm USA, SEO Website OptimizationNext articleA Leading Firm USA, Website SEO & OptimizationAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSThe future Fintech AI & blockchain.February 12, 2021Marketing Mix Data AnalysisApril 17, 2021Global Economy effected CoronavirusApril 15, 2020CRM (Monday.com, Make.com) Data Warehouse Klipfolio DashboardAugust 6, 2023Load moreRECOMMENDED INSIGHTSWhat Creation Taking Creator?How Retail Industry Drive Value Big Data?Impact COVID-19 Engineering Medical College pandemic...OTT platform impact entertainment industry Future. -------------------------------------------------------------------------------- /cleaned_articles/bctech2134.txt: -------------------------------------------------------------------------------- 1 | Title: A Leading Firm USA, SEO Website Optimization - Blackcoffer Insights HomeOur Success StoriesA Leading Firm USA, SEO Website OptimizationOur Success StoriesITA Leading Firm USA, SEO Website OptimizationByAjay Bidyarthy-September 5, 20212799Client BackgroundClient:A leading marketing firm USAIndustry Type:MarketingServices:Marketing consultingOrganization Size:100+Project ObjectiveConnect website Search Console. Add Call Rail CodeProject DescriptionConnecting website Google Search Console Google Tag Manager.Connect website CallRail.Our SolutionWebsite connected Google Search Console successfully.Added CallRail code website.Tools usedkvCoreGoogle Tag ManagerGoogle Search ConsoleCallRailLanguage/techniques usedJavaScriptSkills used:kvCoreGoogle Tag ManagerGoogle Search ConsoleCallRailJavascriptProject SnapshotsProject website URL:https://www.12stonesnwa.com/Previous articleImmigration Datawarehouse & AI-based recommendationsNext articleA Leading Musical Instrumental, Website SEO & OptimizationAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSData Studio Dashboard a data pipeline tool synced Podio...August 25, 2024Big Data solution online multivendor marketplace eCommerce businessJanuary 16, 2022Business Analytics Healthcare IndustryJuly 19, 2019Data Analytics Solution Hospitality IndustryMarch 17, 2020Load moreRECOMMENDED INSIGHTSWhy business need a chatbot?Design develop solution anomaly detection classification problemsGrafana Dashboard visualize analyze sensors’ dataEfficient Processing Analysis Financial Data PDF Files: Addressing... -------------------------------------------------------------------------------- /cleaned_articles/bctech2136.txt: -------------------------------------------------------------------------------- 1 | Title: Lipsync Automation Celebrities Influencers - Blackcoffer Insights HomeOur Success StoriesLipsync Automation Celebrities InfluencersOur Success StoriesEntertainmentLipsync Automation Celebrities InfluencersByAjay Bidyarthy-September 5, 20213393Client BackgroundClient:A leading tech firm IndiaIndustry Type:EntertainmentServices:B2COrganization Size:100+Project ObjectiveTo change lipsing original video new replaced audio.Project DescriptionWe needed create output video will new lipsing according new replaced audio. Also will change actual audio new audio automated editing.Our SolutionWe created two different files will perform 2 different operations 1stwill replace original audio new extract video original. 2ndwill take muted video replaced audio will get output new replaced audio lipsync. done pre-defined model Wav2Lip github.Project Deliverables2 google colab notebooksTools usedgithubGoogle driveLanguage/techniques usedPython 3.6moviepyffmpegModels usedWav2lipSkills usedPython programmingData scienceDatabases usedProvided company (Hrithik Roshan video files)Project SnapshotsProject website urlhttps://colab.research.google.com/drive/18mlREpLmV9hj-uDfufkGJ_-m_E37Hct9?usp=sharinghttps://colab.research.google.com/drive/1FZHvcVKyJxOUkUFI2auPt3vTOu4jh09K?usp=sharingPrevious articleKey Audit Matters Predictive ModelingNext articleImmigration Datawarehouse & AI-based recommendationsAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSAd Networks Marketing Campaign Data Dashboard Looker (Google Data Studio)July 26, 2023Deploy Nodejs app a cloud VM GCP, AWS,...August 8, 2023Should celebrities allowed join politics?April 16, 2020Rising cities impact economy, environment, infrastructure,...August 24, 2023Load moreRECOMMENDED INSIGHTSCOVID-19: countries responding?How Telehealth Telemedicine helping people fight against COVID-19How marketers start integrating AI workHow Secure (SSL) Nginx Let’s Encrypt Ubuntu (Cloud... -------------------------------------------------------------------------------- /cleaned_articles/bctech2138.txt: -------------------------------------------------------------------------------- 1 | Title: Splitting Songs Vocals Instrumental - Blackcoffer Insights HomeOur Success StoriesSplitting Songs Vocals InstrumentalOur Success StoriesEntertainmentITSplitting Songs Vocals InstrumentalByAjay Bidyarthy-September 4, 20213684Client BackgroundClient:A leading Entertainment firm USAIndustry Type:EntertainmentServices:MusicOrganization Size:100+Project ObjectiveThe objective project split a song vocals instrumental.Project DescriptionThe project aims taking a Hindi language song input separating vocals(lyrics) instrumental music song. Save vocals instrumental files separately output.Our SolutionI used Python programming language project. use a Python library called Spleeter developed Deezer made achieve goal.Spleeteris Deezer source separation library pretrained models written Python uses Tensorflow. makes easy train source separation model (assuming a dataset isolated sources), provides already trained state art model performing various flavor separation :Vocals (singing voice) / accompaniment separation (2 stems)Vocals / drums / bass / separation (4 stems)Vocals / drums / bass / piano / separation (5 stems)2 stems 4 stems models high performance themusdbdataset.Spleeteris also fast perform separation audio files 4 stems 100x faster real-time run a GPU.Project DeliverablesPython tool takes Hindi song input gives two audio files output: vocals file instrumental file.Language/techniques usedPythonModels used2 Stems modelSkills usedAdvanced Python programmingProject SnapshotsPrevious articleAI ML technologies Evaluate Learning AssessmentsNext articleKey Audit Matters Predictive ModelingAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSGoogle Local Service Ads Missed Calls Messages Automation ToolAugust 30, 2021QuickBooks dashboard find patterns finance, sales, forecastsSeptember 18, 2021Supplier Insights Decision Supports eCommerce OutletsMarch 23, 2021Ikiga Data, a Global Careers Data Insights PlatformMarch 14, 2021Load moreRECOMMENDED INSIGHTSAd Networks Marketing Campaign Data Dashboard Looker (Google Data Studio)Evolution Advertising IndustryThe future Telehealth services.Deploy view React app(Nextjs) cloud VM GCP,... -------------------------------------------------------------------------------- /cleaned_articles/bctech2143.txt: -------------------------------------------------------------------------------- 1 | Title: Google Local Service Ads (LSA) Data Warehouse - Blackcoffer Insights HomeOur Success StoriesGoogle Local Service Ads (LSA) Data WarehouseOur Success StoriesITGoogle Local Service Ads (LSA) Data WarehouseByAjay Bidyarthy-August 30, 20213394Client BackgroundClient:A leading Marketing firm USAIndustry Type:MarketingServices:Marketing consultingOrganization Size:100+Project ObjectiveAutomated tool extract daily review data Local Service Ads dashboard clients.Project DescriptionExtracts data a company’s Google LSA page last 24 hoursThe data uploaded Bigquery database called “LSA_Review_db”.The script runs a day deployed Heroku name “lsa-daily-reviews”.The script runs companies Google sheet “LSA Review Automation master file”.The following data uploaded:DateCompany NameLocationTotal ReviewsVerified ReviewsOverall StarReviewer NameReview DateReviewer StarReviewer CommentOur SolutionGet list companies monitor along LSA URLUse Selenium automated browsing open review page company.Web scrape data review pagePrepare reportUpload databaseProject DeliverablesAn automated tool runs daily extracts uploads review data companies.Tools usedSeleniumHerokuSheets APIBigQueryLanguage/techniques usedPythonSkills usedData extraction, cleaning summarising. Web scraping.Databases usedBigQuery – LSA_Review_dbWeb Cloud Servers usedHerokuWhat technical Challenges Faced Project ExecutionUsing Selenium automate web browsing since takes a large amount RAM.How Technical Challenges SolvedUsing proper type dynos managing allotment lower costs well memory usage.Previous articleGoogle Local Service Ads Missed Calls Messages Automation ToolNext articleTraction Dashboards Marketing Campaigns PostsAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSWill machine replace human future work?June 24, 2021Centrality Measures & Meaning Network GraphsApril 2, 2021Why scams like Nirav Modi Happen Indian banks?April 12, 2020Big Data Analytics IoT Oil Gas IndustrySeptember 10, 2018Load moreRECOMMENDED INSIGHTSEnhancing Model Accuracy 58% 90%: Strategies Improving...Rise telemedicine Impact Livelihood 2040Deploy view React app(Nextjs) cloud VM GCP,...Rising Cities Impact Economy, Environment, Infrastructure,... -------------------------------------------------------------------------------- /cleaned_articles/bctech2144.txt: -------------------------------------------------------------------------------- 1 | Title: Google Local Service Ads Missed Calls Messages Automation Tool - Blackcoffer Insights HomeOur Success StoriesGoogle Local Service Ads Missed Calls Messages Automation ToolOur Success StoriesITGoogle Local Service Ads Missed Calls Messages Automation ToolByAjay Bidyarthy-August 30, 20213347Client BackgroundClient:A leading Marketing firm USAIndustry Type:MarketingServices:Marketing consultingOrganization Size:100+Project ObjectiveA real time tool send a report missed calls messages client.Project DescriptionExtracts data CallRail database last 5 minutesAll calls marked “missed” messages data sent form a report client.The script runs every 5 minutes deployed Heroku name “missed-messages”.The data collected companies marked red “Missed Messages Notification Automation – Master File” sheet.The following data uploaded:Company NameDateTimeCustomer NameContact No.Customer LocationCall TypeIn case messages:Company NameDateTimeCustomer NameContact No.No. messagesDirection (Inbound/Outbound)ContentOur SolutionTo provide data real time, schedule tool check data every 5 minutes.Extract data CallRailFilter answered callsPrepare reportGet email ids sheetsSend email SendGridProject DeliverablesAn automated tool provides real time updates client along information call.Tools usedHerokuCallRail APISendGridSheets APILanguage/techniques usedPythonSkills usedData extraction, cleaning summarisingDatabases usedGoogle Big QueryWeb Cloud Servers usedHerokuWhat technical Challenges Faced Project ExecutionSending correct reports companies activeHow Technical Challenges SolvedUsing Google Sheet’s cell formatting PythonPrevious articleMarketing Ads Leads Call Status Data Tool BigQueryNext articleGoogle Local Service Ads (LSA) Data WarehouseAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSWhy a severe immunological inflammatory explosion those...March 30, 2020How Login Logout Time Tracking Employees Office done...September 28, 2021Portfolio: Website, Dashboard, SaaS Applications, Web AppsJuly 13, 2022KPI Dashboard AccountantsJuly 21, 2023Load moreRECOMMENDED INSIGHTSKPI Dashboard AccountantsML AI-based insurance premium model predict premium be...Enhancing Model Accuracy 58% 90%: Strategies Improving...COVID-19: countries responding? -------------------------------------------------------------------------------- /cleaned_articles/bctech2145.txt: -------------------------------------------------------------------------------- 1 | Title: Marketing Ads Leads Call Status Data Tool BigQuery - Blackcoffer Insights HomeOur Success StoriesMarketing Ads Leads Call Status Data Tool BigQueryOur Success StoriesITMarketing Ads Leads Call Status Data Tool BigQueryByAjay Bidyarthy-August 30, 20213178Client BackgroundClient:A leading Marketing firm USAIndustry Type:MarketingServices:Marketing consultingOrganization Size:100+Project ObjectivePrepare a daily report companies upload BigQuery database. Data callrail contains call information a company.Project DescriptionExtracts data CallRail database last 24 hoursThe data uploaded Bigquery database called “Call_Status_From_CallRail”.The script runs a day deployed Heroku name “lsa-call-status-db”.The script runs companies CallRail database.The following data uploaded:Company NameStatusLocationCustomer NameCall DateCall TimeContact NoCall StatusCall LeadOur SolutionUse CallRail API get data database.Run script dailyFilter excess dataPrepare reportUpload BigQueryProject DeliverablesA working deployed automated tool runs a day morning hours uploads data BigQuery database. Tool monitored daily.Tools usedHerokuCallRail APIBigQuerySheets APILanguage/techniques usedPythonSkills usedData extraction, cleaning, summarisingDatabases usedBigQuery – Call_Status_From_CallRailWeb Cloud Servers usedHerokuWhat technical Challenges Faced Project ExecutionEnsuring proper data upload databaseHow Technical Challenges SolvedProper monitoring tool post-deployment.Previous articleMarketing Analytics Automate Leads Call Status ReportingNext articleGoogle Local Service Ads Missed Calls Messages Automation ToolAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSTransalta: Migration servers VMware AWS ClientJanuary 16, 2020Financial Modeling Investment Management ProfessionalsAugust 23, 2020Statistical Methods Sales Forecasting Retail IndustryMay 24, 2017Incident Duration Prediction – Infrastructure Real EstateFebruary 27, 2022Load moreRECOMMENDED INSIGHTSAn outlook healthcare year 2040, it...How machine learning used finance banking?Risk Factors Predicting Intraoperative, Postoperative Blood TransfusionRole big data & analytics banking finance -------------------------------------------------------------------------------- /cleaned_articles/bctech2146.txt: -------------------------------------------------------------------------------- 1 | Title: Marketing Analytics Automate Leads Call Status Reporting - Blackcoffer Insights HomeOur Success StoriesMarketing Analytics Automate Leads Call Status ReportingOur Success StoriesITMarketing Analytics Automate Leads Call Status ReportingByAjay Bidyarthy-August 30, 20212604Client BackgroundClient:A leading Marketing firm USAIndustry Type:MarketingServices:Marketing consultingOrganization Size:100+Project ObjectivePrepare a daily report companies upload Google Sheets. Data callrail contains call information a company.Project DescriptionExtracts data CallRail database last 24 hoursThe data uploaded Google sheet “Call status record”The script runs a day deployed Heroku name “call-status-to-sheets”.The script runs companies CallRail database.The following data uploaded:Company NameStatusLocationCustomer NameCall DateCall TimeContact NoCall StatusCall LeadOur SolutionUse CallRail API get data database.Run script dailyFilter excess dataPrepare reportUpload Google SheetsProject DeliverablesA working deployed automated tool runs a day morning hours uploads data Google Sheets. Tool monitored daily.Tools usedHerokuCallRail APIBigQuerySheets APILanguage/techniques usedPythonSkills usedData extraction, cleaning summarisingDatabases usedGoogle Sheets – Call status recordWeb Cloud Servers usedHerokuWhat technical Challenges Faced Project ExecutionEnsuring proper amendment data sheets without overwriteHow Technical Challenges SolvedProper monitoring final deploymentPrevious articleCallRail, Analytics & Leads Report AlertNext articleMarketing Ads Leads Call Status Data Tool BigQueryAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSCRM (Monday.com, Make.com) Data Warehouse Klipfolio DashboardAugust 6, 2023How will COVID-19 affect world work?April 29, 2020INDUSTRIAL REVOLUTION 4.0 – PROS CONSApril 10, 2020Enhancing Front-End Features Functionality Improved User Experience Dashboard...August 26, 2024Load moreRECOMMENDED INSIGHTSHow Connect a Domain Install WordPress Microsoft AzureAre Customer Analytics Driving Big Data Initiatives?How machine learning will affect business?Traceability information – Master data capital -------------------------------------------------------------------------------- /cleaned_articles/bctech2147.txt: -------------------------------------------------------------------------------- 1 | Title: CallRail, Analytics & Leads Report Alert - Blackcoffer Insights HomeOur Success StoriesCallRail, Analytics & Leads Report AlertOur Success StoriesITCallRail, Analytics & Leads Report AlertByAjay Bidyarthy-August 30, 20213167Client BackgroundClient:A leading Marketing firm USAIndustry Type:MarketingServices:Marketing consultingOrganization Size:100+Project ObjectivePrepare annual report companies upload database. Data callrail contains call analytics.Project DescriptionExtracts data CallRail database last 1 year.The data uploaded BigQuery database “lead_report_alert_callrail”The script runs a year deployed Heroku name “lead-report-alert”.Currently, script programmed run 2 companies (on a trial basis) – Capital Law Firm Wilshire Law Firm.The following data uploaded:Company NameNo. calls answeredNo. calls missedNo. calls abandonedNo. calls voicemailTotal CallsOur SolutionUse CallRail API get data database.Set time window one year.Filter excess dataPrepare reportUpload BigQueryProject DeliverablesA working deployed automated tool runs a year morning hours uploads data BigQuery. Tool prototype phase hence operational 2 companies.Tools usedHerokuCallRail APIBigQueryLanguage/techniques usedPythonSkills usedData extraction, cleaning summarisingDatabases usedBigQuery – lead_report_alert_callrailWeb Cloud Servers usedHerokuWhat technical Challenges Faced Project ExecutionWorking a large amount data since a year’s data contains hundred thousands recordsHow Technical Challenges SolvedOptimized code faster processing.Previous articleMarketing Tool Notify Leads Clients Email PhoneNext articleMarketing Analytics Automate Leads Call Status ReportingAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSHow overcome fear making mistakes?August 20, 2020What difference Artificial Intelligence, Machine Learning, Statistics, and...March 9, 2021How COVID-19 crisis redefining jobs services?August 15, 2020Impact AI health medicineFebruary 11, 2021Load moreRECOMMENDED INSIGHTSAuvik, Connectwise integration GrafanaRise telemedicine Impact Livelihood 2040Data Engineering Management tool (Airbyte) custom data connectors to...How Metaverse work Financial Sector? -------------------------------------------------------------------------------- /cleaned_articles/bctech2148.txt: -------------------------------------------------------------------------------- 1 | Title: Marketing Tool Notify Leads Clients Email Phone - Blackcoffer Insights HomeOur Success StoriesMarketing Tool Notify Leads Clients Email PhoneOur Success StoriesITMarketing Tool Notify Leads Clients Email PhoneByAjay Bidyarthy-August 30, 20213145Client BackgroundClient:A leading Marketing firm USAIndustry Type:MarketingServices:Marketing consultingOrganization Size:100+Project ObjectivePrepare a daily report data Local Service Ads dashboard email client.Project DescriptionExtracts data LSA dashboard last 24 hours.The data sent client email form a daily report using SendGrid.The script runs every morning deployed Heroku name “lead-details-to-email”.The data collected companies marked red “Missed Messages Notification Automation – Master File” sheet.The following data uploaded:Number LeadsCost Per LeadLead TypeDispute amount approvedDispute amount approvedCost per CallOur SolutionUse LSA API extract data.Clean data make readable dispose data needed.Get email id company given SheetSend email client using SendGridDeploy HerokuProject DeliverablesA working deployed automated tool runs everyday morning hours sends a report client. Tool monitored everyday.Tools usedHerokuLSA APISendGridSheets APILanguage/techniques usedPythonSkills usedData extraction, cleaning, summarisingDatabases usedData stored sent directly clientWeb Cloud Servers usedHerokuWhat technical Challenges Faced Project ExecutionEnsuring a company’s data go another companyHow Technical Challenges SolvedTesting multiple dummy email idsPrevious articleData ETL: Local Service Ads Leads BigQueryNext articleCallRail, Analytics & Leads Report AlertAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSElectric Vehicles (EV) Load Management System Forecast Energy DemandFebruary 26, 2022Design develop MLops framework Data-centric AIAugust 5, 2023Data ETL: Local Service Ads Leads BigQueryAugust 30, 2021Cloud-Based Web Application Financial Data Processing Visualization S&P...August 25, 2024Load moreRECOMMENDED INSIGHTSPopulation Community Survey AmericaAdvanced Data Visualization Solutions Monitoring Key Business Metrics Integrated,...PPT: Solution quadratic assignment problems (QAP) using Ant Colony SystemA Leading Firm USA, SEO Website Optimization -------------------------------------------------------------------------------- /cleaned_articles/bctech2149.txt: -------------------------------------------------------------------------------- 1 | Title: Data ETL: Local Service Ads Leads BigQuery - Blackcoffer Insights HomeOur Success StoriesData ETL: Local Service Ads Leads BigQueryOur Success StoriesITLifestyle, eCommerce & Online Market PlaceData ETL: Local Service Ads Leads BigQueryByAjay Bidyarthy-August 30, 20213345Client BackgroundClient:A leading Marketing firm USAIndustry Type:MarketingServices:Marketing consultingOrganization Size:100+Project ObjectiveUpload daily data Google Local Service Ads dashboard BigQuery database.Project DescriptionExtracts data LSA dashboard last 24 hours.The data uploaded BigQuery database “lsa_lead_daily_data”The script runs every morning deployed Heroku name “lead-details-to-db”.The data collected companies marked red “Missed Messages Notification Automation – Master File” sheet.The following data uploaded:Number LeadsCost Per LeadLead TypeDispute amount approvedDispute amount approvedCost per CallOur SolutionUse LSA API extract data.Clean data make readable dispose data needed.Upload data a BigQuery database everyday a fixed time.Deploy Heroku run script everyday.Project DeliverablesA working deployed automated tool runs everyday morning hours uploads a report database. Tool monitored everyday.Tools usedHerokuLSA APIBigQuery APISheets APILanguage/techniques usedPythonSkills usedData extraction, cleaning summarisingDatabases usedBigQuery – lsa_lead_daily_dataWeb Cloud Servers usedHerokuWhat technical Challenges Faced Project ExecutionMaking sure data uploaded right company.How Technical Challenges SolvedMonitoring daily logs uploads time making sure data correctPrevious articleMarbles Stimulation using pythonNext articleMarketing Tool Notify Leads Clients Email PhoneAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSEfficient Data Integration User-Friendly Interface Development: Navigating Challenges Web...March 17, 2024Coronavirus: Impact Hospitality IndustryMay 1, 2020Analyze Fraudulent Call Data Stream Analytics Visualize Results in...March 16, 2021Blockchain PaymentsSeptember 7, 2019Load moreRECOMMENDED INSIGHTSDeploy MERN google app engine, google cloud platformEnhancing Data Collection Research Institutions: Addressing Survey Fatigue Incorporating...Enhancing Model Accuracy 58% 90%: Strategies Improving...Building Analytics Dashboard a PDF Parsing Pipeline Data... -------------------------------------------------------------------------------- /cleaned_articles/bctech2155.txt: -------------------------------------------------------------------------------- 1 | Title: Healthcare Data Analysis - Blackcoffer Insights HomeOur Success StoriesHealthcare Data AnalysisOur Success StoriesHealthcareHealthcare Data AnalysisByAjay Bidyarthy-August 22, 20213427Client BackgroundClient:A leading healthcare tech firm USAIndustry Type:Healthcare ConsultingServices:Management consultantOrganization Size:100+Project ObjectiveThe main objective project find pattern vital signs patients admitted hospital past. pattern, get ranges help us give early warnings.Project DescriptionWe interested non-survivor patients’ vital signs compare survivor patients. find patterns invital signsthat could better determine patient died (ex. Sp02 70, patient 95% cases died, Sp02 50%, death rate 99.9%) take correlations help us find better patterns define death cases.Data dataset used analysis taken mimic website. dataset correct format want, manipulation, get data ready analysis.Our SolutionApproachTo protect patient confidentiality date time shifted future that’s actual time shifted time column create extra column hour tells us time passed hours since first observation ICU.After manipulation final dataset contain vital signs values observation patients time separate column also label fo Death (0 1) another column.There two options deal missing valuesDrop rows contain null values.2.Fill missing values method using pandas.I can’t go 1st option a major part data missing values. so, I decided go second option fill missing values average upper lower values. that, I filtered data take patients’ data died a hospital survive.Project DeliverablesAfter performing EDA also include removal impossible outliers, come a result Analysis.This result helps build early warning system predict condition patients basis score, calculated condition using vital sign values.Tools usedGoogle Colab NotebookLanguage/techniques usedPythonSkills usedData visualizationData analysisPandasNumpySeabornDatabases usedSQLMongoDBWeb Cloud Servers usedGoogle CloudProject SnapshotsProject website urlhttps://colab.research.google.com/drive/1mo7i32BoEVb0Ac6_CWwJd7_HVbliktx0?usp=sharingPrevious articleELK Stack – Elastic QueriesNext articleGoogle LSA API Data Automation DashboardingAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSHow Data Analytics help business respond impact...May 1, 2021Statistical Methods Sales Forecasting Retail IndustryMay 24, 2017Healthcare AI ChatBot using LLAMA, LLM, LangchainJuly 3, 2024Is big data AI?July 20, 2021Load moreRECOMMENDED INSIGHTSBig Data Analytics Help form Political Leaders Win ElectionCallRail, Analytics & Leads Report AlertStudent Database Management SystemData Warehouse Google Data Studio (Looker) Dashboard -------------------------------------------------------------------------------- /cleaned_articles/bctech2156.txt: -------------------------------------------------------------------------------- 1 | Title: Budget, Sales KPI Dashboard using Power BI - Blackcoffer Insights HomeOur Success StoriesBudget, Sales KPI Dashboard using Power BIOur Success StoriesBanking, Financials, Securities, InsuranceLifestyle, eCommerce & Online Market PlaceBudget, Sales KPI Dashboard using Power BIByAjay Bidyarthy-July 29, 20214419Project DescriptionWeekly Data – clustered bar chart weekly Budget & Actual value , weekly Total Budget & Actual value (completed)YTD Data – clustered bar chart monthly Budget & Actual value , monthly Total Budget & Actual value (completed)Sales History – stacked chart yearly sales month sales , total yearly sale (completed)Dashlet – weekly data – Total weekly Budget , Total weekly Actual , % weekly Budget (completed)Dashlet – YTD data – Total YTD Budget , Total YTD Actual , % YTD Budget (completed)Dashlet – Sales History – Total Sales (completed)Filters – select Area , select City , select Years (completed)Data Visualization DeliverablesPresentationMapDashboardAPI IntegrationData Visualization ToolsKibanaGoogle Data StudioMicrosoft ExcelMicrosoft Power BIData Visualization LanguagesJavaScriptSQLPythonDAXDemoPrevious articleBenefits Big Data Different fieldsNext articleELK Stack – Elastic QueriesAjay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSReal life data analysis stationary non-stationary Time SeriesFebruary 18, 2019Data security Protect a major enterprise assetJune 12, 2019Driving Insights Largest Community Investors TradersOctober 8, 2020Efficient Processing Analysis Financial Data PDF Files: Addressing...August 25, 2024Load moreRECOMMENDED INSIGHTSStreamlined Equity Waterfall Calculation Deal Management SystemA web-based dashboard filtered data retrieval land recordsRising Cities Impact Economy, Environment, Infrastructure,...Transforming Insurance Claim Processing Automation & Artificial Intelligence -------------------------------------------------------------------------------- /cleaned_articles/bctech2157.txt: -------------------------------------------------------------------------------- 1 | Title: Amazon Buy Bot, Automation AI tool Auto-Checkouts - Blackcoffer Insights HomeOur Success StoriesAmazon Buy Bot, Automation AI tool Auto-CheckoutsOur Success StoriesLifestyle, eCommerce & Online Market PlaceAmazon Buy Bot, Automation AI tool Auto-CheckoutsByAjay Bidyarthy-June 26, 20213262Client BackgroundClient:A leading consulting firm USAIndustry Type:ConsultingServices:Management consultantOrganization Size:100+Project ObjectiveThe main objective project build automation tool buy product amazon.Project DescriptionThis project basically completed using selenium Python. done write a python script automation using Selenium.Make clicks use logics check item stock not. item stock buys product otherwise repeat process again.Our SolutionA simple python code uses selenium web driver work.Project DeliverablesPython CodeTools usedSelenium WebdriverLanguage/techniques usedPythonSkills usedWeb ScrapingSeleniumProject SnapshotsPrevious articlePredictive Modelling, AI, ML Dashboards Power BINext articleHow Big Data Help Finance Growth Large Firms?Ajay BidyarthyRELATED ARTICLESMORE AUTHORAI ML-Based YouTube Analytics Content Creation Tool Optimizing Subscriber Engagement Content StrategyEnhancing Front-End Features Functionality Improved User Experience Dashboard Accuracy Partner Hospital ApplicationROAS Dashboard Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSModeling & Simulation Drug Development & FormulationJanuary 9, 2019ELK Stack – Elastic QueriesAugust 20, 2021NER Task using BERT data XML-formatAugust 5, 2023Rising Cities Impact Economy, Environment, Infrastructure,...August 18, 2023Load moreRECOMMENDED INSIGHTSHow AI will impact future work?Sentiment Analysis a Leading Restaurants Chain USAAI Dashboard Health Fitness – In-Depth LookDo Social Media Owned Meta? -------------------------------------------------------------------------------- /cleaned_articles/desktop.ini: -------------------------------------------------------------------------------- 1 | [.ShellClassInfo] 2 | IconResource=C:\Program Files\Google\Drive File Stream\97.0.1.0\GoogleDriveFS.exe,26 3 | -------------------------------------------------------------------------------- /desktop.ini: -------------------------------------------------------------------------------- 1 | [.ShellClassInfo] 2 | IconResource=C:\Program Files\Google\Drive File Stream\97.0.1.0\GoogleDriveFS.exe,26 3 | -------------------------------------------------------------------------------- /extracted_articles/bctech2041.txt: -------------------------------------------------------------------------------- 1 | Title: Design and develop Jenkins shared library - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesDesign and develop Jenkins shared libraryOur Success StoriesITDesign and develop Jenkins shared libraryByAjay Bidyarthy-August 6, 20232701Client BackgroundClient:A leading tech firm in the USAIndustry Type:ITServices:SaaS, ProductsOrganization Size:100+The ProblemCreate Jenkins shared library for the following:validate AWS AMI creationcheck if network rules exist in aws EC2check if the security group in aws EC2Our SolutionWe created a Jenkins shared library in which we are using AWS  ec2 describe-images command with the help of aws cli if an ami don’t exist than describe-images throws errorWe created a Jenkins shared library in which we are using aws ec2 describe-network-acls  for validating we were comparing input name with VPCWe created a Jenkins shared library in which we are using aws ec2  describe-instances for validating we were checking input name with SecurityGroups groupDeliverablesJenkins LibrariesTools usedVS Code IDEJenkinsAWSLanguage/techniques usedGrovvySkills usedJenkinsAWS ServerWeb Cloud Servers usedAWSProject SnapshotsProject VideoContact DetailsHere are my contact details:Email: ajay@blackcoffer.comSkype: asbidyarthyWhatsApp: +91 9717367468Telegram: @asbidyarthyFor project discussions and daily updates, would you like to use Slack, Skype, Telegram, or Whatsapp? Please recommend, what would work best for you.Previous articleDesign and develop retool app for wholecell.io and Asana data using their api’sNext articleDesign and develop PowerShell scriptAjay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSAutoGPT SetupMay 10, 2023Impacts of COVID 19 on Streets Sides Food StallsNovember 6, 2021Deploy MERN to google app engine, google cloud platformMay 16, 2021Transforming the Healthcare SystemsApril 17, 2021Load moreRECOMMENDED INSIGHTSAn outlook of healthcare by the year 2040, and how it...Marketing Analytics – Why do we care about it?Healthcare AI ChatBot using LLAMA, LLM, LangchainLipsync Automation for Celebrities and Influencers -------------------------------------------------------------------------------- /extracted_articles/bctech2042.txt: -------------------------------------------------------------------------------- 1 | Title: Design and develop retool app for wholecell.io and Asana data using their api’s - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesDesign and develop retool app for wholecell.io and Asana data using their...Our Success StoriesITDesign and develop retool app for wholecell.io and Asana data using their api’sByAjay Bidyarthy-August 6, 20232576Client BackgroundClient:A leading tech firm in the USAIndustry Type:ITServices:SaaS, ProductsOrganization Size:100+The ProblemCreate retool app for wholecell.io and Asana data using their api’sOur SolutionWe have created two table one table contain data from wholecell.io platform and another table contain data from Assna.In that wholecell.io table we are providing:Order idOrder statusOrder channelOrganizationLink of the OrderIn Assna Table we are providing following details:Id of the taskName of the taskResource typeResource_subtypeCallerPo-idAs client data from wholecell and Assna was linked client can search the order by PO-id in Assna tableDeliverablesApp in retoolTools usedRetoolLanguage/techniques usedJavaScriptSkills usedRetoolAPI integrationJavaScriptWhat are the technical Challenges Faced during Project ExecutionApi was not providing all required details according to the client requirement and there were less options for data pre-processing as retool only javascriptHow the Technical Challenges were SolvedWe had fetched details from one api and provide id to the other api using JavaScript this was done by using javascript promise methodWe also had to do some string manipulation to get data according the client requirementContact DetailsHere are my contact details:Email: ajay@blackcoffer.comSkype: asbidyarthyWhatsApp: +91 9717367468Telegram: @asbidyarthyFor project discussions and daily updates, would you like to use Slack, Skype, Telegram, or Whatsapp? Please recommend, what would work best for you.Previous articleDesign and develop a retool app that will show stock and crypto related information using IEX APINext articleDesign and develop Jenkins shared libraryAjay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSDeploy and view React app(Nextjs) on cloud VM such as GCP,...August 8, 2023How AI will help the Defense Power of a country?June 26, 2021Role of Big Data in Cyber Security: A Shotgun Against Rising...June 11, 2017Why is there a severe immunological and inflammatory explosion in those...March 30, 2020Load moreRECOMMENDED INSIGHTSHow Retail Industry Drive Value from Big Data?Changing landscape and emerging trends in the Indian IT/ITeS Industry.Impacts of COVID 19 on Food productsOff-Page SEO -------------------------------------------------------------------------------- /extracted_articles/bctech2046.txt: -------------------------------------------------------------------------------- 1 | Title: Qualtrics API integration using Python - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesQualtrics API integration using PythonOur Success StoriesQualtrics API integration using PythonByAjay Bidyarthy-August 5, 20232631Client BackgroundClient:A leading tech firm in the USAIndustry Type:ITServices:SaaS, ProductsOrganization Size:100+The ProblemAPI Integration to read/write data in SQL tables from an online application.Our SolutionTo write the api between qualtrics and sql server using python programming language.Solution ArchitectureFig. System ArchitectureDeliverablesPython SoftwareDocumentationTools usedPythonQualtricsModels usedPandasRequestsnumpyZipfileiopyodbcSkills usedExtract Transfer LoadDatabases usedSQL ServerWhat are the technical Challenges Faced during Project ExecutionDuring the project execution, we faced the following challenges:After data integration, the content of the file was not readable.Mapping the values with the required columns.How the Technical Challenges were SolvedTo solve the technical challenges, we provided the following solutions as follow:To get the content into the CSV format after integration we used the Io module to get the text content.To get the mapping values we created the CSV file and store the record in it and fetch that record to the SQl.Business ImpactUsing this script the client can now fetch the Qualtrics data into the SQL server automatically after every 1 hour.Project SnapshotsFig. Data in CSV FormatFig. Data in Table formFig. SQL dataProject website urlGithub:  https://github.com/AjayBidyarthy/Richi-S-apiProject VideoContact DetailsHere are my contact details:Email: ajay@blackcoffer.comSkype: asbidyarthyWhatsApp: +91 9717367468Telegram: @asbidyarthyFor project discussions and daily updates, would you like to use Slack, Skype, Telegram, or Whatsapp? Please recommend, what would work best for you.Previous articleDesign and develop MLops framework for Data-centric AINext articleNER Task using BERT with data in XML-formatAjay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSEffective Management of Social Media Data Extraction: Strategies for Authentication, Security,...March 17, 2024COVID-19 Impact on Hospitality IndustryMay 1, 2020Deploy Nodejs app on a cloud VM such as GCP, AWS,...August 8, 2023Replacing existing pavement roads, parking lots and sidewalks with pavement made...July 17, 2019Load moreRECOMMENDED INSIGHTSRise of Chatbots and its impact on customer support by the...React Native Apps in the Development PortfolioAuvik, Connectwise integration in GrafanaHow to protect future data and its privacy? -------------------------------------------------------------------------------- /extracted_articles/bctech2048.txt: -------------------------------------------------------------------------------- 1 | Title: NLP-based Approach for Data Transformation - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesNLP-based Approach for Data TransformationOur Success StoriesITNLP-based Approach for Data TransformationByAjay Bidyarthy-July 29, 20232744Client BackgroundClient:A leading tech firm in the USAIndustry Type:ITServices:SaaS, ProductsOrganization Size:100+The ProblemPerforming Readability and Quality testing on the text corpus from text filesOur SolutionThe intention was to create a tool/system that can consume text files through a given csv file having a path for all the text files through this csv file our tool should be able to read all files one by one and could perform some tests and analysis on that text data and output the results in a csv format presenting all the metrics.In order to achieve this goal we created a Python-based ready-to-use code that will read all text files presented in the given csv files and perform 14 different evaluations on that text data and save the results in a excel and csv based format.Solution ArchitectureDeliverablesThe final deliverable was the tool/system/code for processing and evaluation text.Language/techniques usedPythonNatural Language processing technique used for text evaluationSkills usedPython ProgrammingWhat are the technical Challenges Faced during Project ExecutionThe architecture of the solution for this project problem statement was simple, no challenges were faced during the execution of the project.Contact DetailsHere are my contact details:Email: ajay@blackcoffer.comSkype: asbidyarthyWhatsApp: +91 9717367468Telegram: @asbidyarthyFor project discussions and daily updates, would you like to use Slack, Skype, Telegram, or Whatsapp? Please recommend, what would work best for you.Previous articleAn ETL tool to pull data from Shiphero to Google Bigquery Data WarehouseNext articleDesign and develop MLops framework for Data-centric AIAjay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSLipsync Automation for Celebrities and InfluencersSeptember 5, 2021Transforming the Healthcare SystemsApril 17, 2021Deploy Nodejs app on a cloud VM such as GCP, AWS,...August 8, 2023How Telehealth and Telemedicine helping people to fight against COVID-19April 28, 2022Load moreRECOMMENDED INSIGHTSUsing People Analytics To Drive Business PerformanceAnalyzing the Impact of Female CEO Appointments on Company Stock PricesEmbedding care robots into society and practice: Socio-technical considerationsThe Metaverse and its Implications for our Digital Future. -------------------------------------------------------------------------------- /extracted_articles/bctech2066.txt: -------------------------------------------------------------------------------- 1 | Title: AI agent development and Deployment in Jina AI - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesAI agent development and Deployment in Jina AIOur Success StoriesITAI agent development and Deployment in Jina AIByAjay Bidyarthy-July 24, 20232639Client BackgroundClient:A leading tech firm in EuropeIndustry Type:ITServices:IT and ConsultingOrganization Size:100+The ProblemThe client’s object was to create AI agents for his website, which the end-users will utilize for many tasks. The client had some recommendations on the models are utilized.Our SolutionCreated a feasible models list that complements the client’s requirement and when ahead and executed the Executor code for every model for compatibility with JinaAI deployment. After implementing Executor codes, I created a Flow to connect every executor and deployed it successfully.DeliverablesSuccessfully delivered executable deployed models in Jina AiTools usedJina AI, VSCode, HuggingFaceLanguage/techniques usedPythonModels usedWhisper, Stable Diffusion, GPT3, Codex, YOLO, CoquiAI, PDF SegmentorSkills usedPython, Model APIsDatabases usedJinaAI CloudWhat are the technical Challenges Faced during Project ExecutionThere were minute challenges, such as deployment issues and Execution issuesHow the Technical Challenges were SolvedI resolved the issues effectively after long hours of understanding the concept because JinaAI is a new growing technology that does not have many forums to solve errors and issues.Project SnapshotsProject VideoContact DetailsHere are my contact details:Email: ajay@blackcoffer.comSkype: asbidyarthyWhatsApp: +91 9717367468Telegram: @asbidyarthyFor project discussions and daily updates, would you like to use Slack, Skype, Telegram, or Whatsapp? Please recommend, what would work best for you.Previous articleGolden Record – A knowledge graph database approach to unfold discovery using Neo4jNext articleAI Solutions for Foreign Exchange – An Automated Algo Trading ToolAjay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSAn ETL solution for an Internet Publishing firmJuly 26, 2023Which one is better AI or big data?July 19, 2021Big Data Analytics through IoT in Oil and Gas IndustrySeptember 10, 2018Coronavirus impact on energy marketsMay 1, 2020Load moreRECOMMENDED INSIGHTSImpacts of COVID 19 on Food productsImpact of COVID-19 pandemic on office space and co-working industries.Building Custom TFLite Models and Benchmarking on VOXL2 ChipsHow are people diverted to Telehealth services and telemedicine? -------------------------------------------------------------------------------- /extracted_articles/bctech2069.txt: -------------------------------------------------------------------------------- 1 | Title: Create a Knowledge Graph to Provide Real-time Analytics, Recommendations, and a Single Source of Truth - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesCreate a Knowledge Graph to Provide Real-time Analytics, Recommendations, and a Single...Our Success StoriesITRetail & Supply ChainCreate a Knowledge Graph to Provide Real-time Analytics, Recommendations, and a Single Source of TruthByAjay Bidyarthy-July 22, 20232587Client BackgroundClient:A leading tech firm in the USAIndustry Type:RetailServices:Retail BusinessOrganization Size:100+The ProblemThe Client was using NoSql Database which was slow and did not provide real-time response for complex queries. The data had many Connections and it was difficult to represent them in NoSQL or Relational Databases.Our SolutionCreate a Knowledge Graph and Provide Real-time Analytics and Recommendations using Machine Learning.Solution ArchitectureNeo4j was Installed on a Cloud VM based on Linodes.DeliverablesKnowledge graphs and Data Pipelines are used to Populate the Graph.API’s to Perform CRUD operations in real-time.Tools usedNeo4jPostmanLanguage/techniques usedPythonJSONModels usedNode-Relationship modelSkills usedProgrammingData EngineeringData AnalyticsDatabases usedNeo4jWeb Cloud Servers usedLinodeWhat are the technical Challenges Faced during Project ExecutionIntegration of Firestore with Neo4j without any native integration method or driver.How the Technical Challenges were SolvedThe challenge was solved by using api to retrieve data from Firestore.Project SnapshotsContact DetailsHere are my contact details:Email: ajay@blackcoffer.comSkype: asbidyarthyWhatsApp: +91 9717367468Telegram: @asbidyarthyFor project discussions and daily updates, would you like to use Slack, Skype, Telegram, or Whatsapp? Please recommend, what would work best for you.Previous articleAdvanced AI for Thermal Person DetectionNext articleAdvanced AI for Trading AutomationAjay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSHow does Big Data Help in Finance and the Growth of...July 19, 2021Design and develop retool app for wholecell.io and Asana data using...August 6, 2023How Retail Industry Drive Value from Big Data?July 25, 2017Securing Sensitive Financial Data with Privacy-Preserving Machine Learning for Predictive AnalyticsAugust 25, 2024Load moreRECOMMENDED INSIGHTSData science – Create Tailored algorithmsIs big data the same as AI?Travel and Tourism OutlookHow robots can help in e-learning platforms? -------------------------------------------------------------------------------- /extracted_articles/bctech2070.txt: -------------------------------------------------------------------------------- 1 | Title: Advanced AI for Thermal Person Detection - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesAdvanced AI for Thermal Person DetectionOur Success StoriesInfrastructure & Real EstateProduction & ManufacturingAdvanced AI for Thermal Person DetectionByAjay Bidyarthy-July 22, 20232635Client BackgroundClient:A leading tech firm in the Middle EastIndustry Type:SecurityServices:Security servicesOrganization Size:100+The ProblemDetect a Person from thermal image and videos. Why this model was created was not told to us by the client.Our SolutionUse Deeplearning Computer Vision to train the model on custom dataset and get the results.Solution ArchitectureLinux 22.04Nvidiva RTX 3080DeliverablesTrained modelTools usedLabelimgYolov7COCO2JSONLanguage/techniques usedPythonModels usedYolov7Skills usedDeeplearningComputer visionProgrammingContact DetailsHere are my contact details:Email: ajay@blackcoffer.comSkype: asbidyarthyWhatsApp: +91 9717367468Telegram: @asbidyarthyFor project discussions and daily updates, would you like to use Slack, Skype, Telegram, or Whatsapp? Please recommend, what would work best for you.Previous articleAdvanced AI for Road Cam Threat DetectionNext articleCreate a Knowledge Graph to Provide Real-time Analytics, Recommendations, and a Single Source of TruthAjay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSCreate a Knowledge Graph to Provide Real-time Analytics, Recommendations, and a...July 22, 2023An AI ML-based web application that detects the correctness of text...July 8, 2022Blockchain for PaymentsSeptember 7, 2019How to Connect a Domain and Install WordPress on Microsoft AzureFebruary 15, 2020Load moreRECOMMENDED INSIGHTSWhat is the difference between Artificial Intelligence, Machine Learning, Statistics, and...Algorithmic trading for multiple commodities markets, like Forex, Metals, Energy, etc.An app for updating the email id of the user and...AI-driven data analysis AI tool using Langchain for a leading real... -------------------------------------------------------------------------------- /extracted_articles/bctech2071.txt: -------------------------------------------------------------------------------- 1 | Title: Advanced AI for Road Cam Threat Detection - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesAdvanced AI for Road Cam Threat DetectionOur Success StoriesInfrastructure & Real EstateProduction & ManufacturingAdvanced AI for Road Cam Threat DetectionByAjay Bidyarthy-July 22, 20232613Client BackgroundClient:A leading tech firm in the Middle EastIndustry Type:SecurityServices:Security servicesOrganization Size:100+The ProblemDetect the threat level of accidents between a Pedestrian and a Car.Our SolutionUse Deeplearning Computer vision and logic to detect the threat level as defined by the Client.Solution ArchitectureLinux 22.04DeliverablesProgram which detects the threat level.Pretrained model.Tools usedYolov7DEEPSORTOpencvLanguage/techniques usedPythonModels usedYolov7Skills usedProgrammingComputer VisionDeep learningWhat are the technical Challenges Faced during Project ExecutionIntegration of Object tracking algorithm with Object detection algorithm.Writing of logic to detect the threat level.How the Technical Challenges were SolvedThe technical challenge was sorted by testing, experimenting and later on finding and modifying an already existing repository to use as a baseline for our code for integration.Contact DetailsHere are my contact details:Email: ajay@blackcoffer.comSkype: asbidyarthyWhatsApp: +91 9717367468Telegram: @asbidyarthyFor project discussions and daily updates, would you like to use Slack, Skype, Telegram, or Whatsapp? Please recommend, what would work best for you.Previous articleAdvanced AI for Pedestrian Crossing SafetyNext articleAdvanced AI for Thermal Person DetectionAjay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSDatabase Normalization & Segmentation with Google Data Studio Dashboard InsightsFebruary 27, 2022Streamlined Equity Waterfall Calculation and Deal Management SystemMarch 16, 2024Data Management ServicesSeptember 11, 2020Easy Database AccessJune 8, 2019Load moreRECOMMENDED INSIGHTSInterpret the Coefficients in Regression ModelsiOS Mobile Applications PortfolioDriving Insights from the Largest Community for Investors and TradersSteps to Meta-Analysis -------------------------------------------------------------------------------- /extracted_articles/bctech2072.txt: -------------------------------------------------------------------------------- 1 | Title: Advanced AI for Pedestrian Crossing Safety - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesAdvanced AI for Pedestrian Crossing SafetyOur Success StoriesInfrastructure & Real EstateProduction & ManufacturingAdvanced AI for Pedestrian Crossing SafetyByAjay Bidyarthy-July 22, 20232621Client BackgroundClient:A leading tech firm in the Middle EastIndustry Type:SecurityServices:Security servicesOrganization Size:100+The ProblemTraffic Signals are inefficient because even if there are no cars or no pedestrians on the road it still works on a timer and stops the traffic or pedestrian unnecessarily.Our SolutionWe provide a Computer vision-logic to Manipulate the traffic signal to work such that it turns red only when x number of pedestrians are waiting to cross the signal.Solution ArchitectureYolov7 pose estimationOpencvDeliverablesThe program Detects Pedestrians and Gives alerts to traffic Signals to turn Red or stay Green.Yolov7 pose model weightsTools usedYolov7OpencvLanguage/techniques usedPythonComputer VisionModels usedYolov7 Pose EstimationSkills usedProgrammingComputer VisionDeep LearningWhat are the technical Challenges Faced during Project ExecutionThere was no existing solution and we had to create the logic from scratch.How the Technical Challenges were SolvedResearching Computer Vision. Learning new Techniques and Experimentation.Project SnapshotsContact DetailsHere are my contact details:Email: ajay@blackcoffer.comSkype: asbidyarthyWhatsApp: +91 9717367468Telegram: @asbidyarthyFor project discussions and daily updates, would you like to use Slack, Skype, Telegram, or Whatsapp? Please recommend, what would work best for you.Previous articleAdvanced AI for Handgun DetectionNext articleAdvanced AI for Road Cam Threat DetectionAjay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSMedical ClassificationSeptember 16, 2022Methodology for ETL Discovery Tool using LLMA, OpenAI, LangchainFebruary 27, 2024Marketing Analytics Solution, a Big Data ApproachMay 1, 2019Global Economy effected by CoronavirusApril 15, 2020Load moreRECOMMENDED INSIGHTSHow you lead a project or a team without any technical...Data Studio Dashboard with a data pipeline tool synced with Podio...Data Warehouse to Google Data Studio (Looker) DashboardRole of Big Data in Cyber Security: A Shotgun Against Rising... -------------------------------------------------------------------------------- /extracted_articles/bctech2073.txt: -------------------------------------------------------------------------------- 1 | Title: Advanced AI for Handgun Detection - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesAdvanced AI for Handgun DetectionOur Success StoriesInfrastructure & Real EstateITProduction & ManufacturingAdvanced AI for Handgun DetectionByAjay Bidyarthy-July 21, 20232700Client BackgroundClient:A leading tech firm in the Middle EastIndustry Type:SecurityServices:Security servicesOrganization Size:100+The ProblemDetecting Handguns in images and videos.Our SolutionWe use Yolov7 instance segmentation model to detect and provide coordinates for handguns.Solution ArchitectureLinux 22.04YoloDeliverablesTrained model of yolov7 instance segmentationTools usedOpenimagesRoboflowYolov7Language/techniques usedPythonModels usedYolov7_maskSkills usedDeeplearningProgrammingWhat are the technical Challenges Faced during Project ExecutionRetrieving handgun images in bulk from opensource.How the Technical Challenges were SolvedFound Openimages dataset with good amount of required imagesContact DetailsHere are my contact details:Email: ajay@blackcoffer.comSkype: asbidyarthyWhatsApp: +91 9717367468Telegram: @asbidyarthyFor project discussions and daily updates, would you like to use Slack, Skype, Telegram, or Whatsapp? Please recommend, what would work best for you.Previous articleUsing Graph Technology to Create Single Customer View.Next articleAdvanced AI for Pedestrian Crossing SafetyAjay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSAdvanced AI for Pedestrian Crossing SafetyJuly 22, 2023What is the future of mobile apps?February 12, 2021Off-Page SEOSeptember 18, 2020Marbles Stimulation using pythonAugust 30, 2021Load moreRECOMMENDED INSIGHTSNew Jersey Based Micro Business Sentiment AnalysisDesign and develop PowerShell scriptGoogle LSA API Data Automation and DashboardingAI Bot Driven by GraphDB Neo4j for a Leading Healthcare Tech... -------------------------------------------------------------------------------- /extracted_articles/bctech2074.txt: -------------------------------------------------------------------------------- 1 | Title: Using Graph Technology to Create Single Customer View. - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesUsing Graph Technology to Create Single Customer View.Our Success StoriesFast Moving Consumer GoodsRetail & Supply ChainUsing Graph Technology to Create Single Customer View.ByAjay Bidyarthy-July 21, 20232641Client BackgroundClient:A leading retail firm in NewzealandIndustry Type:RetailServices:Retail businessOrganization Size:100+The ProblemCompanies face issue of having a Single customer under various rows with slightly different information in the same database. This causes unwanted duplication and inaccurate statistics. It also results in inaccurate ad targeting and financial loss.Our SolutionWe leverage graph technology to create a single customer view by using Complex cypher queries  and Graph Algorithms.Solution ArchitectureWe have an Azure VM on which we have installed the Neo4j Database. Deployment architecture is a single Instance because of using the Community version of the software.DeliverablesPopulated Neo4j Database.Required Cypher Queries.Tools usedNeo4jGraphlyticsLanguage/techniques usedJavaCypher QueryModels usedNode-Relationship modelSkills usedData AnalyticsData EngineeringData ScienceDatabases usedNeo4jWeb Cloud Servers usedAZUREWhat are the technical Challenges Faced during Project ExecutionOnly 1 Difficulty was faced in this Project and that was to migrate data from Elasticsearch to Neo4j.How the Technical Challenges were SolvedResearch and Experimentation.Project SnapshotsContact DetailsHere are my contact details:Email: ajay@blackcoffer.comSkype: asbidyarthyWhatsApp: +91 9717367468Telegram: @asbidyarthyFor project discussions and daily updates, would you like to use Slack, Skype, Telegram, or Whatsapp? Please recommend, what would work best for you.Previous articleCar Detection in Satellite ImagesNext articleAdvanced AI for Handgun DetectionAjay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSData from CRM via Zapier to Google Sheets (Dynamic) to PowerBIJuly 29, 2023How to access Amazon Seller Central or Vendor Central data in...March 3, 2021Advantages and Disadvantages of E-learning during the COVID-19 for students and...December 7, 2021How Artificial Intelligence can deliver real value to companies?October 15, 2018Load moreRECOMMENDED INSIGHTSIntegration of video-conferencing data to the existing web appReplacing existing pavement roads, parking lots and sidewalks with pavement made...Transform API into SDK library and widgetAI, ML, and IoT driven Entry Management and Monitoring -------------------------------------------------------------------------------- /extracted_articles/bctech2084.txt: -------------------------------------------------------------------------------- 1 | Title: Trading Bot for FOREX - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesTrading Bot for FOREXOur Success StoriesBanking, Financials, Securities, and InsuranceTrading Bot for FOREXByAjay Bidyarthy-December 31, 20223111Client BackgroundClient:A Leading Trading Firm in the USAIndustry Type:FinanceServices:Trading, ConsultingOrganization Size:100+The ProblemAutomate trading on the MT4 terminal for forex when certain conditions are met, and end trade at the best exit point.Save mt4 forex data for a instrument live for every tick.Our SolutionUse PyTrader to log into trading system (mt4) for 2 brokers.Use live prices to identify when prices diverge.Buy one currency on broker 1, sell currency on broker 2.Hold until prices come back together.Coded a MQL4 script that will save tick data (bid, ask, open, high, low, close) for any instrument when activeSolution ArchitectureDeliverablesPython Script to Automate the two Meta Trader 4 terminals, and trade when some conditions are true and break the trade at a exit point.A MQL4 Sript that will Save the Live tick data (Bid, Ask, Spread, Open, High, Low, Close) in a CSV file.Tools usedPyTradernumpypandasLanguage/techniques usedPython(Automation)Mql4(To save tick data)Business ImpactClient requirements were  to automate his forex trading strategy  on Meta Trader4 terminal, so that he doesn’t have to bother trading anymore, the Python script we designed to not only do it, plus it offers a safe exit point for Ongoing Trades, that saved the client’s money and time.Previous articlePython model for the analysis of sector-specific stock ETFs for investment purposesNext articleAlgorithmic trading for multiple commodities markets, like Forex, Metals, Energy, etc.Ajay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSContinued Demand for SustainabilityNovember 30, 2019Predictive Modelling, AI, ML Dashboards in Power BIJune 26, 2021Recommendation Engine for Insurance Sector to Expand Business in the Rural...July 29, 2023Can robots tackle late-life loneliness?December 2, 2020Load moreRECOMMENDED INSIGHTSAdvance Analytics for Refocusing ProfitsPrediction Model for Online CasinoHow Artificial Intelligence can deliver real value to companies?ETL Pipeline -------------------------------------------------------------------------------- /extracted_articles/bctech2092.txt: -------------------------------------------------------------------------------- 1 | Title: Transform API into SDK library and widget - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesTransform API into SDK library and widgetOur Success StoriesHealthcareITTransform API into SDK library and widgetByAjay Bidyarthy-September 15, 20222607Client BackgroundClient:A Leading Tech Firm in the USAIndustry Type:ITServices:Consulting, Marketing, HealthtechOrganization Size:500+Project ObjectiveConvert API documentation into SDK library and widget. Expected deliverables are SDK library and widgets forWeb appsiOS appsAndroid AppsProject DescriptionAPI documentation is available for a tool that allows customers to type in their medication and find the cheapest price near them. For partners who want to have it on their own site, currently using the API documentation but would like to ultimately be able to send them an embeddable widget that incorporates the tool on their siteOur SolutionWe created a flutter widget that uses  SDK libraries that allows the customer to type their medication and find the cheapest price near them.This widget can be embedded in their web, android and IOS applicationsProject Deliverables1)SDK Library/Widget2)Sample flutter applicationTools usedFlutterLanguage/techniques usedDartSkills used1)Knowledge of dart language2)flutter app developingWhat are the technical Challenges Faced during Project Execution1 )Problems while fetching details of drugs and pharmacies2) Showing details of drugs and pharmacies in the widgetHow the Technical Challenges were SolvedAll technical challenges are solved by proper communication with the client and by logical analyzing of dataProject SnapshotsProject Videohttps://www.youtube.com/watch?v=MyNK_DPtsKA&ab_channel=BlackcofferPrevious articleIntegration of a product to a cloud-based CRM platformNext articleAn agent-based model of a Virtual Power Plant (VPP)Ajay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSPrediction Model for Online CasinoApril 5, 2021How Political Leaders will Shape Tomorrow using Big Data & AnalyticsApril 15, 2019Design and develop Jenkins shared libraryAugust 6, 2023Streamlined Equity Waterfall Calculation and Deal Management SystemMarch 16, 2024Load moreRECOMMENDED INSIGHTSDriving Insights from the Largest Community for Investors and TradersPower BI Dashboard on Operations, Transactions, and Marketing Data, embedding the...Rise of Cybercrime and its Effect in upcoming FutureThe workflow of a Machine Learning / Artificial Intelligence project -------------------------------------------------------------------------------- /extracted_articles/bctech2096.txt: -------------------------------------------------------------------------------- 1 | Title: Design & develop an app in retool which shows the progress of the added video - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesDesign & develop an app in retool which shows the progress of...BlackcofferOur Success StoriesITDesign & develop an app in retool which shows the progress of the added videoByAjay Bidyarthy-August 24, 20222566Client BackgroundClient:A Leading Tech Firm in the USAIndustry Type:IT & ConsultingServices:Software, Business Solutions, ConsultingOrganization Size:200+Project DescriptionThe objective was to develop a progress bar that can help costumes to estimate the analytics of the video.Our SolutionThe client wanted a progress bar with the following filters:Date filter: – Update the progress bar and count of the videos according to the date selectedCategory filter: – Update the progress bar and the count of the videos according to the selected categoryWe have created a SQL query for getting a count of the videos from the full video table according to the filter selected in the appIn added video table some columns were missing to solve this we created a SQL query for joining the added video table to the other tables and return the count of the video according to the filter selectedProject DeliverablesApp in retoolTools usedRetoolLanguage/techniques usedSQLSkills usedSQLDatabases usedSQL DatabaseWhat are the technical Challenges Faced during Project ExecutionClient wanted date filter and a video category filter but this data was not there in added video tableHow the Technical Challenges were SolvedWe had to join multiple data so that we can get category column and date column for applying filterProject SnapshotsProject VideoPrevious articleRise of Electric Vehicles and its Impact on Livelihood by 2040Next articleIntegration of video-conferencing data to the existing web appAjay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSHow to Setup Custom Domain for Google App Engine Application?February 13, 2021What Analytics & IT Outsourcing engagement model is right for you?August 2, 2018Deploy node.js apps to google app engine, google cloud platformMay 16, 2021Transforming Insurance Claim Processing with Automation & Artificial IntelligenceApril 25, 2019Load moreRECOMMENDED INSIGHTSSupplier Insights and Decision Supports for the eCommerce OutletsBig Data Analytics through IoT in Oil and Gas IndustryThe future of InvestingHow marketers can start integrating AI in their work -------------------------------------------------------------------------------- /extracted_articles/bctech2106.txt: -------------------------------------------------------------------------------- 1 | Title: Optimize the data scraper program to easily accommodate large files and solve OOM errors - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesOptimize the data scraper program to easily accommodate large files and solve...Our Success StoriesITOptimize the data scraper program to easily accommodate large files and solve OOM errorsByAjay Bidyarthy-May 13, 20222661Client BackgroundClient:A leading tech firm in IndiaIndustry Type:IT ServicesServices:SAAS services, Marketing services, Business consultantOrganization Size:100+Project DescriptionBuilding a large data warehouse that houses projects and tenders data from all over the world that is to be collected from official government websites, multilateral banks, state and local government agencies, data aggregating websites, etc.Our SolutionWe had tried multiple solutions to prevent the program from running out of memory. We used python pandas techniques to control the use of memory which worked for some files and did not work for others. Provided more solutions using vaex ,dask module and datatables.Project DeliverablesDesired changes to the code and committing them to github.Tools usedVscodePythonGithubSlackLanguage/techniques usedChunkingdask Dataframevaexdatatablepython.Skills usedCloudPythonTime complexityWhat are the technical Challenges Faced during Project ExecutionSystem specs requirement was the main issue during this project because the RAM available was too less and got used up quickly.How the Technical Challenges were SolvedTeam viewer to use remote desktop which had higher specs would be sufficient enough to solve the problem.Business ImpactProvided various techniques to solve memory issues.Suggested parallel programming to decrease the execution time by 12% making getting the tender data at a much faster rate.Project SnapshotsProject website urlhttps://github.com/Taiyo-ai/opentenders-euhttps://opentender.euPrevious articleMaking a robust way to sync data from airtables to mongoDB using python – ETL SolutionNext articleNFT Data Automation (looksrare), and ETL toolAjay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSHow is Login Logout Time Tracking for Employees in Office done...September 28, 2021Transforming the Healthcare SystemsApril 17, 2021AI in healthcare to Improve Patient OutcomesJune 26, 2021Code Review ChecklistApril 10, 2020Load moreRECOMMENDED INSIGHTSElectric Vehicles (EV) Load Management System to Forecast Energy DemandAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing...How Metaverse will change your life?Data Transformation -------------------------------------------------------------------------------- /extracted_articles/bctech2110.txt: -------------------------------------------------------------------------------- 1 | Title: Database Normalization & Segmentation with Google Data Studio Dashboard Insights - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesDatabase Normalization & Segmentation with Google Data Studio Dashboard InsightsOur Success StoriesITDatabase Normalization & Segmentation with Google Data Studio Dashboard InsightsByAjay Bidyarthy-February 27, 20222817Client BackgroundClient:A leading marketing firm in the USAIndustry Type:Market ResearchServices:Marketing, ConsultancyOrganization Size:60+Project ObjectiveTo combine the different datasets.To make dashboards for each and every dataset individually.Project DescriptionPhase – 1: In this project first of all we have to combine different datasets individually to make single file for each source.Phase – 2: Make Good looking reports for each file individually.Our SolutionWe used pandas dataframe to combine different files to make single file for each source. We used Google Data Studio to make good looking and better reports with good UI.Project DeliverablesWe have provided a Google Data Studio report file as deliverable for the project.Tools usedPython, Google Data Studio, Google ChromeLanguage/techniques usedPython Programming and SQL queries editor.Models usedSDLC model used in this project. We have used the SDLC model as analysis, design, implementation, testing and maintenance.Skills usedData cleaning, Data Pre-processing, Data Visualisation are used in this project.Databases usedWe have used the traditional file systems as database storage.What are the technical Challenges Faced during Project ExecutionCombining Data sets into single file.Making good looking UI dashboards.How the Technical Challenges were SolvedI used pandas dataframe to combine different datasets and made a single file of every individual source. I used Google Data Studio to make dashboard for the project.Project SnapshotsProject VideoPrevious articlePower BI dashboard to drive insights from complex data to generate business insightsNext articleStatistical Data Analysis of Reinforced ConcreteAjay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSMarketing Drives Results With A Focus On ProblemsNovember 25, 2019Design & develop an app in retool which shows the progress...August 24, 2022Behavior Based Chi-Square model to Detect Data-Exfiltration over the NetworkMay 15, 2017Rise of Internet Demand and Its Impact on Communications and Alternatives...August 17, 2023Load moreRECOMMENDED INSIGHTSAn outlook of healthcare by the year 2040, and how it...Estimating the impact of COVID-19 on the world of workData TransformationPharmaceutical Data Power BI Report -------------------------------------------------------------------------------- /extracted_articles/bctech2114.txt: -------------------------------------------------------------------------------- 1 | Title: Power BI Data-Driven Map Dashboard - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesPower BI Data-Driven Map DashboardOur Success StoriesITPower BI Data-Driven Map DashboardByAjay Bidyarthy-February 26, 20223210Client BackgroundClient:A leading marketing firm in the USAIndustry Type:Market ResearchServices:Marketing, ConsultancyOrganization Size:60+Project ObjectiveChange bubble colors dynamically.Make table and charts linked. If a user clicks on tables values, then the bubble chart on the map should be highlighted that relates to the table.Project Description“I have a map visual. I would like to dynamically change the colours of some of the bubbles.”The report page has several filters and KPI Dashboard, whose metrics change dynamically when the user clicks a certain element. Similarly the map should also change dynamically relative to the filter.Our SolutionAdded the website data from Details table to the map visualization, it makes the bubbles get coloured dynamically according to the requirement for websites data.Project DeliverablesThe Power BI ( .pbix ) file updated with solutionTools usedPower BISkills usedPower BIData VisualizationData AnalysisDatabases usedThe database that came in with the Power BI file received from clientWhat are the technical Challenges Faced during Project ExecutionThe map was not linkedMap Bubbles were not dynamicHow the Technical Challenges were SolvedRefactoring the data model and using appropriate keys to link the data togetherThat made Map to change according to Slicers/FiltersTo Change the colour, Bookmark buttons were used in the dashboard to bring up the dynamic colour changing with slicing (works after being published)Project SnapshotsProject VideoPrevious articleAI Conversational Bot using RASANext articleElectric Vehicles (EV) Load Management System to Forecast Energy DemandAjay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSLessons from the past: Some key learnings relevant to the coronavirus...May 1, 2020Internet Demand’s Evolution, Communication Impact, and 2035’s Alternative PathwaysAugust 18, 2023Management challenges for future digitalization of healthcare servicesDecember 2, 2020Interpret the Coefficients in Regression ModelsApril 4, 2019Load moreRECOMMENDED INSIGHTSHow prepared is India to tackle a possible COVID-19 outbreak?Coronavirus: Effect on the Hospitality IndustryTransforming the Healthcare SystemsHow is Login Logout Time Tracking for Employees in Office done... -------------------------------------------------------------------------------- /extracted_articles/bctech2118.txt: -------------------------------------------------------------------------------- 1 | Title: Microsoft Azure chatbot with LUIS (Language Understanding) - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesMicrosoft Azure chatbot with LUIS (Language Understanding)Our Success StoriesLifestyle, eCommerce & Online Market PlaceMicrosoft Azure chatbot with LUIS (Language Understanding)ByAjay Bidyarthy-January 24, 20222988Client BackgroundClient:A leading retail firm in the USAIndustry Type:RetailServices:e-commerce, retail businessOrganization Size:100+Project ObjectiveTo create an advanced chatbot using Microsoft Azure cognitive service to take orders from customer on behalf of a pizza restaurant and give order summary as end result to the user.Project DescriptionThe project uses MS Azure LUIS service for language understanding to receive order details from a customer and provide an order summary. Also display various menu options to the customer in a dynamic method.Our SolutionOur solution is to create a chatbot on MS Azure platform using their LUIS service in bot-framework composer environment. Use dynamic hero cards to display menu so that user can get a better experience.Project DeliverablesChatbotTools usedBot Framework composerBot emulatorMS Azure LUIS servicesLanguage/techniques usedBot framework composerNatural language processingModels usedMS Azure LUISMS Azure QnAMS Azure speed SDKSkills usedDeep learningWeb developmentCloud techWeb Cloud Servers usedMicrosoft Azure web platformWhat are the technical Challenges Faced during Project ExecutionMonthly quota for LUIS authoring service was reachedTracking multiple items ordered by userAccessing relevant images for each menu itemHow the Technical Challenges were SolvedSwitching to a more suitable pricing tier which would have to eventually switch to when move onto production phaseCreating custom functions and intents for different trackersUsing open license images from internetProject SnapshotsProject website urlDemoPrevious articleDo All Social Media Is Owned By Meta?Next articleMetaBridges API Decentraland Integration – AR, VRAjay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSBank Risk Management in IndiaJune 1, 2019Advanced AI for Thermal Person DetectionJuly 22, 2023Blockchain in FintechSeptember 14, 2019Digital Strategic Foresight Platform – Smart AI-Driven DashboardFebruary 22, 2019Load moreRECOMMENDED INSIGHTSEmbedding care robots into society and practice: Socio-technical considerationsWill Machine Replace The Human in the Future of Work?How does artificial intelligence affect the environmentGrafana Dashboard to visualize and analyze sensors’ data -------------------------------------------------------------------------------- /extracted_articles/bctech2124.txt: -------------------------------------------------------------------------------- 1 | Title: Creating a custom report and dashboard using the data got from Atera API - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesCreating a custom report and dashboard using the data got from Atera...Our Success StoriesITCreating a custom report and dashboard using the data got from Atera APIByAjay Bidyarthy-January 16, 20223084Client BackgroundClient:A leading Marketing firm in USAIndustry Type:MarketingServices:Marketing, consulting, ads, business solutionsOrganization Size:20+Project DescriptionAtera.com is used as our RMM, we have an agent on every machine. Which tracks the if a machine goes down, initial response time etc.., The website doesn’t provide any standard reports, So we needed to create a custom report.Our SolutionImporting the data from Atera API into JupyterUsing Web Scraping download the JSON dataConvert the JSON data to Data Frame and download it into PC.Clean the data with only required columnsUpload the data into google sheets.Connect google sheets and google data studioCreate the dashboard with the dataTools usedPython (Pandas, requests)Google SheetsGoogle Data StudioSkills usedAnalyticsProgramming LanguageDatabases usedContacts.csvCustomers.csvTickets.csvAlerts.csvWhat are the technical Challenges Faced during Project Execution?I found it difficult on downloading the data.How the Technical Challenges were SolvedOnce I figured I have been using the wrong Authorization key to login I was able to solve the issue, and convert the curl command into pythonProject SnapshotsProject website urlhttps://datastudio.google.com/reporting/5e61aecb-a420-41cc-afba-d0ca37f69132Project VideoPrevious articleAzure Data Lake and Power BI DashboardNext articleBig Data solution to an online multivendor marketplace eCommerce businessAjay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSMicrosoft Azure chatbot with LUIS (Language Understanding)January 24, 2022AI Chatbot using LLM, Langchain, LLamaJuly 7, 2024Interpret the Coefficients in Regression ModelsApril 4, 2019Python model for the analysis of sector-specific stock ETFs for investment...December 31, 2022Load moreRECOMMENDED INSIGHTSHow Metaverse is Shaping the Future?Optimize the data scraper program to easily accommodate large files and...Datawarehouse, and Recommendations Engine for AirBNBData ETL: Local Service Ads Leads to BigQuery -------------------------------------------------------------------------------- /extracted_articles/bctech2129.txt: -------------------------------------------------------------------------------- 1 | Title: React Native Apps in the Development Portfolio - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesReact Native Apps in the Development PortfolioOur Success StoriesITReact Native Apps in the Development PortfolioByAjay Bidyarthy-September 6, 20214106Here are the list of react native apps developed by the team and the resources:https://itunes.apple.com/us/app/truckmap-truck-gps-routes/id1198422047?mt=8https://play.google.com/store/apps/details?id=com.truckmap.truckmaphttps://play.google.com/store/apps/details?id=com.verifai.standalonehttps://apps.apple.com/nl/app/verifai/id1504214033https://apps.apple.com/de/app/meetlist-lokale-aktivit%C3%A4ten/id1439183715https://play.google.com/store/apps/details?id=de.mlug.meetlisthttps://play.google.com/store/apps/details?id=com.payroo.employeehttps://play.google.com/store/apps/details?id=com.vahcarehttps://play.google.com/store/apps/details?id=com.candorivfPrevious articleA Leading Law Firm in the USA, Website SEO & OptimizationNext articleMarketing, sales, and financial data business dashboard (Wink Report)Ajay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSIntegration of Python and Power BI, Python as an External Tool...June 26, 2021Do Ethnic differences possibly influence the risk of Multiple Sclerosis development...June 4, 2019Advanced AI for Pedestrian Crossing SafetyJuly 22, 2023Centrality Measures & Their Meaning from the Network GraphsApril 2, 2021Load moreRECOMMENDED INSIGHTSCloud-Based Data Modeling and Analysis Platform with Drag-and-Drop Interface and OpenAI...Data Integration for MarketersAI Dashboard of Health Fitness – In-Depth LookIoT & AI/ML Solution for Gas Stations -------------------------------------------------------------------------------- /extracted_articles/bctech2130.txt: -------------------------------------------------------------------------------- 1 | Title: A Leading Law Firm in the USA, Website SEO & Optimization - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesA Leading Law Firm in the USA, Website SEO & OptimizationOur Success StoriesITA Leading Law Firm in the USA, Website SEO & OptimizationByAjay Bidyarthy-September 5, 20213276Client BackgroundClient:A leading marketing firm in the USAIndustry Type:MarketingServices:Marketing consultingOrganization Size:100+Project ObjectiveConnect website to Search Console, Google Analytics and Facebook Pixel through Google Tag Manager.Fix SEO of the website.Project DescriptionConnecting website to Google Search Console, Google Analytics and Facebook Pixel through Google Tag Manager.Fixing SEO of the website.Our SolutionWebsite connected to Google Search Console, Google Analytics and Facebook Pixel successfully.Fixed themeta description errorbroken link error404 error, etc.Tools usedSquarespaceGoogle Tag ManagerGoogle AnalyticsGoogle Search ConsoleLanguage/techniques usedJavaScriptSkills usedSquarespaceGoogle Tag ManagerGoogle AnalyticsGoogle Search ConsoleJavaScriptProject SnapshotsProject website URLhttps://www.keepingorlandomoving.com/Previous articleA Leading Hospitality Firm in the USA, Website SEO & OptimizationNext articleReact Native Apps in the Development PortfolioAjay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSIMPACT OF COVID-19 ON THE GLOBAL ECONOMYApril 13, 2020How to overcome your fear of making mistakes?August 20, 2020Impact of coronavirus on the Indian economyApril 15, 2020Transforming and Managing a Large-Scale SQL Pedigree Database to Neo4j Graph...August 25, 2024Load moreRECOMMENDED INSIGHTSCOVID-19: How have countries been responding?COVID-19 Impact on Hospitality IndustryHow will COVID-19 affect the world of work?E-commerce Store Analysis – Purchase Behavior, Ad Spend, Conversion, Traffic, etc… -------------------------------------------------------------------------------- /extracted_articles/bctech2131.txt: -------------------------------------------------------------------------------- 1 | Title: A Leading Hospitality Firm in the USA, Website SEO & Optimization - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesA Leading Hospitality Firm in the USA, Website SEO & OptimizationOur Success StoriesITA Leading Hospitality Firm in the USA, Website SEO & OptimizationByAjay Bidyarthy-September 5, 20213262Client BackgroundClient:A leading marketing firm in the USAIndustry Type:MarketingServices:Marketing consultingOrganization Size:100+Project ObjectiveWorking On-page SEO of the pages to make it user-friendly and feasible for crawlers to make the site indexing better.Project DescriptionFirstly, exploring the Liverez as it was a new platform then, performing intermediate SEO like page titles and description, completing word count, alt. text and removing duplicate page title and description.Our SolutionTo increase the organic traffic of the site and improve the insights.Project DeliverablesThere was a bit of improvement in the traffic of the site.Tools usedBrightlocal.com, Yoast SEO, GrammarlyLanguage/techniques usedBasic HTMLSkills usedON-page SEOProject SnapshotsProject website urlhttps://www.missionbeach.com/Previous articleA Leading Firm in the USA, Website SEO & OptimizationNext articleA Leading Law Firm in the USA, Website SEO & OptimizationAjay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSMethodology for ETL Discovery Tool using LLMA, OpenAI, LangchainFebruary 27, 2024iOS Mobile Applications PortfolioJune 23, 2021Automated Job Data Import and Management Solution for Enhanced EfficiencyAugust 25, 2024Add SPF Record, Cpanel, BigrockAugust 17, 2019Load moreRECOMMENDED INSIGHTSBuilding an Analytics Dashboard with a PDF Parsing Pipeline for Data...Time Series Analysis and Trend Forecasting Solution for Predicting News TrendsUsing Graph Technology to Create Single Customer View.iOS Mobile Applications Portfolio -------------------------------------------------------------------------------- /extracted_articles/bctech2132.txt: -------------------------------------------------------------------------------- 1 | Title: A Leading Firm in the USA, Website SEO & Optimization - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesA Leading Firm in the USA, Website SEO & OptimizationOur Success StoriesITA Leading Firm in the USA, Website SEO & OptimizationByAjay Bidyarthy-September 5, 20213062Client BackgroundClient:A leading marketing firm in the USAIndustry Type:MarketingServices:Marketing consultingOrganization Size:100+Project ObjectiveFixing On-Page SEO of the websiteProject DescriptionFixing On-Page SEO contains things like title, meta description, image-alt text, broken links, 404 error page, multiple h1 tag in one page, duplicate title/description, dynamic URL, sparse content page (word count <500), etc.Our SolutionFixed all the possible solutions that we can do for improving the SEO health score.Fixed, image-alt text error, title, meta description, broken links, dynamic URL, 404 error page, sparse content pages, contact information on all pages, connecting website with Google search console.Tools usedAhrefsWordPressGoogle Search ConsoleLanguage/techniques usedHTMLRedirection pluginSkills usedHTMLWordPressGoogle Search ConsoleProject SnapshotsProject website URLURLhttps://www.jupiteroutdoorcenter.com/HomePrevious articleA Leading Musical Instrumental, Website SEO & OptimizationNext articleA Leading Hospitality Firm in the USA, Website SEO & OptimizationAjay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSHow the COVID-19 crisis is redefining jobs and services?August 15, 2020Oil prices by the year 2040, and how it will impact...August 20, 2022AI in healthcare to Improve Patient OutcomesJune 26, 2021An outlook of healthcare by the year 2040, and how it...August 20, 2022Load moreRECOMMENDED INSIGHTSAirbnb & Homeaway Pricing RecommendationImpress with a Modern WebsiteData TransformationAnalytics in Healthcare Industry -------------------------------------------------------------------------------- /extracted_articles/bctech2133.txt: -------------------------------------------------------------------------------- 1 | Title: A Leading Musical Instrumental, Website SEO & Optimization - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesA Leading Musical Instrumental, Website SEO & OptimizationOur Success StoriesITProduction & ManufacturingA Leading Musical Instrumental, Website SEO & OptimizationByAjay Bidyarthy-September 5, 20212994Client BackgroundClient:A leading marketing firm in the USAIndustry Type:MarketingServices:Marketing consultingOrganization Size:100+Project ObjectiveConnect website to Google Tag Manager.Remove error.Project DescriptionRemove all previously added code and add new code for connecting to Google Tag Manager.Remove 5xx error from the website.Our SolutionWebsite connected to Google Tag Manager successfully.Removed 5xx error.Tools usedGoogle Tag ManagerWordPressLanguage/techniques usedJavaScriptSkills usedWordPressGoogle Tag ManagerProject website URLURL:https://www.hamiltonpianoco.com/Previous articleA Leading Firm in the USA, SEO and Website OptimizationNext articleA Leading Firm in the USA, Website SEO & OptimizationAjay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSThe future of Fintech AI & blockchain.February 12, 2021Marketing Mix Data AnalysisApril 17, 2021Global Economy effected by CoronavirusApril 15, 2020CRM (Monday.com, Make.com) to Data Warehouse to Klipfolio DashboardAugust 6, 2023Load moreRECOMMENDED INSIGHTSWhat if the Creation is Taking Over the Creator?How Retail Industry Drive Value from Big Data?Impact of COVID-19 on Engineering and Medical College during this pandemic...OTT platform and its impact on the entertainment industry in Future. -------------------------------------------------------------------------------- /extracted_articles/bctech2134.txt: -------------------------------------------------------------------------------- 1 | Title: A Leading Firm in the USA, SEO and Website Optimization - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesA Leading Firm in the USA, SEO and Website OptimizationOur Success StoriesITA Leading Firm in the USA, SEO and Website OptimizationByAjay Bidyarthy-September 5, 20212799Client BackgroundClient:A leading marketing firm in the USAIndustry Type:MarketingServices:Marketing consultingOrganization Size:100+Project ObjectiveConnect website to Search Console. Add Call Rail CodeProject DescriptionConnecting website to Google Search Console through Google Tag Manager.Connect website with CallRail.Our SolutionWebsite connected to Google Search Console successfully.Added CallRail code to the website.Tools usedkvCoreGoogle Tag ManagerGoogle Search ConsoleCallRailLanguage/techniques usedJavaScriptSkills used:kvCoreGoogle Tag ManagerGoogle Search ConsoleCallRailJavascriptProject SnapshotsProject website URL:https://www.12stonesnwa.com/Previous articleImmigration Datawarehouse & AI-based recommendationsNext articleA Leading Musical Instrumental, Website SEO & OptimizationAjay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSData Studio Dashboard with a data pipeline tool synced with Podio...August 25, 2024Big Data solution to an online multivendor marketplace eCommerce businessJanuary 16, 2022Business Analytics In The Healthcare IndustryJuly 19, 2019Data Analytics Solution for the Hospitality IndustryMarch 17, 2020Load moreRECOMMENDED INSIGHTSWhy does your business need a chatbot?Design and develop solution to anomaly detection classification problemsGrafana Dashboard to visualize and analyze sensors’ dataEfficient Processing and Analysis of Financial Data from PDF Files: Addressing... -------------------------------------------------------------------------------- /extracted_articles/bctech2136.txt: -------------------------------------------------------------------------------- 1 | Title: Lipsync Automation for Celebrities and Influencers - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesLipsync Automation for Celebrities and InfluencersOur Success StoriesEntertainmentLipsync Automation for Celebrities and InfluencersByAjay Bidyarthy-September 5, 20213393Client BackgroundClient:A leading tech firm in IndiaIndustry Type:EntertainmentServices:B2COrganization Size:100+Project ObjectiveTo change the lipsing of the original video with the new replaced audio.Project DescriptionWe needed to create an output video that will have the new lipsing according to the new replaced audio. Also we will have to change the actual audio with the new audio with automated editing.Our SolutionWe have created two different files which will perform 2 different operations 1stwill replace the original audio with new and extract only video from original. 2ndwill take the muted video and replaced audio and we will get the output of the new replaced audio lipsync. This is done by pre-defined model Wav2Lip on github.Project Deliverables2  google colab notebooksTools usedgithubGoogle driveLanguage/techniques usedPython 3.6moviepyffmpegModels usedWav2lipSkills usedPython programmingData scienceDatabases usedProvided by the company (Hrithik Roshan video files)Project SnapshotsProject website urlhttps://colab.research.google.com/drive/18mlREpLmV9hj-uDfufkGJ_-m_E37Hct9?usp=sharinghttps://colab.research.google.com/drive/1FZHvcVKyJxOUkUFI2auPt3vTOu4jh09K?usp=sharingPrevious articleKey Audit Matters Predictive ModelingNext articleImmigration Datawarehouse & AI-based recommendationsAjay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSAd Networks Marketing Campaign Data Dashboard in Looker (Google Data Studio)July 26, 2023Deploy Nodejs app on a cloud VM such as GCP, AWS,...August 8, 2023Should celebrities be allowed to join politics?April 16, 2020Rising IT cities and its impact on the economy, environment, infrastructure,...August 24, 2023Load moreRECOMMENDED INSIGHTSCOVID-19: How have countries been responding?How Telehealth and Telemedicine helping people to fight against COVID-19How marketers can start integrating AI in their workHow To Secure (SSL) Nginx with Let’s Encrypt on Ubuntu (Cloud... -------------------------------------------------------------------------------- /extracted_articles/bctech2138.txt: -------------------------------------------------------------------------------- 1 | Title: Splitting of Songs into its Vocals and Instrumental - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesSplitting of Songs into its Vocals and InstrumentalOur Success StoriesEntertainmentITSplitting of Songs into its Vocals and InstrumentalByAjay Bidyarthy-September 4, 20213684Client BackgroundClient:A leading Entertainment firm in the USAIndustry Type:EntertainmentServices:MusicOrganization Size:100+Project ObjectiveThe objective of this project is to split a song into its vocals and instrumental.Project DescriptionThe project aims at taking a Hindi language song as input and separating the vocals(lyrics) from the instrumental music of the song. Save both the vocals and instrumental files separately as output.Our SolutionI have used Python programming language for this project. The use of a Python library called Spleeter developed by Deezer has been made to achieve our goal.Spleeteris Deezer source separation library with pretrained models written in Python and uses Tensorflow. It makes it easy to train source separation model (assuming you have a dataset of isolated sources), and provides already trained state of the art model for performing various flavor of separation :Vocals (singing voice) / accompaniment separation (2 stems)Vocals / drums / bass / other separation (4 stems)Vocals / drums / bass / piano / other separation (5 stems)2 stems and 4 stems models have high performance on themusdbdataset.Spleeteris also very fast as it can perform separation of audio files to 4 stems 100x faster than real-time when run on a GPU.Project DeliverablesPython tool that takes Hindi song as input and gives two audio files as output: vocals file and instrumental file.Language/techniques usedPythonModels used2 Stems modelSkills usedAdvanced Python programmingProject SnapshotsPrevious articleAI and ML technologies to Evaluate Learning AssessmentsNext articleKey Audit Matters Predictive ModelingAjay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSGoogle Local Service Ads Missed Calls and Messages Automation ToolAugust 30, 2021QuickBooks dashboard to find patterns in finance, sales, and forecastsSeptember 18, 2021Supplier Insights and Decision Supports for the eCommerce OutletsMarch 23, 2021Ikiga Data, a Global Careers Data and Insights PlatformMarch 14, 2021Load moreRECOMMENDED INSIGHTSAd Networks Marketing Campaign Data Dashboard in Looker (Google Data Studio)Evolution of Advertising IndustryThe future of Telehealth services.Deploy and view React app(Nextjs) on cloud VM such as GCP,... -------------------------------------------------------------------------------- /extracted_articles/bctech2143.txt: -------------------------------------------------------------------------------- 1 | Title: Google Local Service Ads (LSA) Data Warehouse - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesGoogle Local Service Ads (LSA) Data WarehouseOur Success StoriesITGoogle Local Service Ads (LSA) Data WarehouseByAjay Bidyarthy-August 30, 20213394Client BackgroundClient:A leading Marketing firm in the USAIndustry Type:MarketingServices:Marketing consultingOrganization Size:100+Project ObjectiveAutomated tool to extract daily review data from Local Service Ads dashboard for all clients.Project DescriptionExtracts data from a company’s Google LSA page for the last 24 hoursThe data is uploaded to the Bigquery database called “LSA_Review_db”.The script runs once a day and is deployed to Heroku by the name “lsa-daily-reviews”.The script runs for all companies in the Google sheet “LSA Review Automation master file”.The following data is uploaded:DateCompany NameLocationTotal ReviewsVerified ReviewsOverall StarReviewer NameReview DateReviewer StarReviewer CommentOur SolutionGet list of companies to monitor along with their LSA URLUse Selenium automated browsing to open the review page for each company.Web scrape the data from the review pagePrepare reportUpload to databaseProject DeliverablesAn automated tool that runs daily and extracts and uploads review data for all companies.Tools usedSeleniumHerokuSheets APIBigQueryLanguage/techniques usedPythonSkills usedData extraction, cleaning and summarising. Web scraping.Databases usedBigQuery –  LSA_Review_dbWeb Cloud Servers usedHerokuWhat are the technical Challenges Faced during Project ExecutionUsing Selenium to automate web browsing since it takes a large amount of RAM.How the Technical Challenges were SolvedUsing the proper type of dynos and managing their allotment to lower both costs as well as memory usage.Previous articleGoogle Local Service Ads Missed Calls and Messages Automation ToolNext articleTraction Dashboards of Marketing Campaigns and PostsAjay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSWill machine replace the human in the future of work?June 24, 2021Centrality Measures & Their Meaning from the Network GraphsApril 2, 2021Why scams like Nirav Modi Happen with Indian banks?April 12, 2020Big Data Analytics through IoT in Oil and Gas IndustrySeptember 10, 2018Load moreRECOMMENDED INSIGHTSEnhancing Model Accuracy from 58% to Over 90%: Strategies for Improving...Rise of telemedicine and its Impact on Livelihood by 2040Deploy and view React app(Nextjs) on cloud VM such as GCP,...Rising IT Cities and its Impact on the Economy, Environment, Infrastructure,... -------------------------------------------------------------------------------- /extracted_articles/bctech2144.txt: -------------------------------------------------------------------------------- 1 | Title: Google Local Service Ads Missed Calls and Messages Automation Tool - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesGoogle Local Service Ads Missed Calls and Messages Automation ToolOur Success StoriesITGoogle Local Service Ads Missed Calls and Messages Automation ToolByAjay Bidyarthy-August 30, 20213347Client BackgroundClient:A leading Marketing firm in the USAIndustry Type:MarketingServices:Marketing consultingOrganization Size:100+Project ObjectiveA real time tool to send a report of missed calls and messages to the client.Project DescriptionExtracts data from CallRail database for the last 5 minutesAll the calls which are marked as “missed” and all messages in the data are sent in the form of a report to the client.The script runs every 5 minutes and is deployed to Heroku by the name “missed-messages”.The data is collected only for the companies that are not marked in red in the “Missed Messages Notification Automation – Master File” sheet.The following data is uploaded:Company NameDateTimeCustomer NameContact No.Customer LocationCall TypeIn case of messages:Company NameDateTimeCustomer NameContact No.No. of messagesDirection (Inbound/Outbound)ContentOur SolutionTo provide data real time, schedule the tool to check for data every 5 minutes.Extract data from CallRailFilter out all answered callsPrepare reportGet email ids from sheetsSend email through SendGridProject DeliverablesAn automated tool which provides real time updates to the client along with all information about the call.Tools usedHerokuCallRail APISendGridSheets APILanguage/techniques usedPythonSkills usedData extraction, cleaning and summarisingDatabases usedGoogle Big QueryWeb Cloud Servers usedHerokuWhat are the technical Challenges Faced during Project ExecutionSending correct reports only to the companies which are activeHow the Technical Challenges were SolvedUsing Google Sheet’s cell formatting in PythonPrevious articleMarketing Ads Leads Call Status Data Tool to BigQueryNext articleGoogle Local Service Ads (LSA) Data WarehouseAjay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSWhy is there a severe immunological and inflammatory explosion in those...March 30, 2020How is Login Logout Time Tracking for Employees in Office done...September 28, 2021Portfolio: Website, Dashboard, SaaS Applications, Web AppsJuly 13, 2022KPI Dashboard for AccountantsJuly 21, 2023Load moreRECOMMENDED INSIGHTSKPI Dashboard for AccountantsML and AI-based insurance premium model to predict premium to be...Enhancing Model Accuracy from 58% to Over 90%: Strategies for Improving...COVID-19: How have countries been responding? -------------------------------------------------------------------------------- /extracted_articles/bctech2145.txt: -------------------------------------------------------------------------------- 1 | Title: Marketing Ads Leads Call Status Data Tool to BigQuery - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesMarketing Ads Leads Call Status Data Tool to BigQueryOur Success StoriesITMarketing Ads Leads Call Status Data Tool to BigQueryByAjay Bidyarthy-August 30, 20213178Client BackgroundClient:A leading Marketing firm in the USAIndustry Type:MarketingServices:Marketing consultingOrganization Size:100+Project ObjectivePrepare a daily report for the companies and upload it to BigQuery database. Data is from callrail and contains all call information about a company.Project DescriptionExtracts data from CallRail database for the last 24 hoursThe data is uploaded to the Bigquery database called “Call_Status_From_CallRail”.The script runs once a day and is deployed to Heroku by the name “lsa-call-status-db”.The script runs for all companies in the CallRail database.The following data is uploaded:Company NameStatusLocationCustomer NameCall DateCall TimeContact NoCall StatusCall LeadOur SolutionUse CallRail API to get data from database.Run script dailyFilter out excess dataPrepare reportUpload to BigQueryProject DeliverablesA working deployed automated tool that runs once a day in the morning hours and uploads the data to BigQuery database. Tool is monitored daily.Tools usedHerokuCallRail APIBigQuerySheets APILanguage/techniques usedPythonSkills usedData extraction, cleaning, and summarisingDatabases usedBigQuery –  Call_Status_From_CallRailWeb Cloud Servers usedHerokuWhat are the technical Challenges Faced during Project ExecutionEnsuring proper data upload to databaseHow the Technical Challenges were SolvedProper monitoring of tool post-deployment.Previous articleMarketing Analytics to Automate Leads Call Status and ReportingNext articleGoogle Local Service Ads Missed Calls and Messages Automation ToolAjay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSTransalta: Migration of servers from VMware to AWS ClientJanuary 16, 2020Financial Modeling of the Investment Management ProfessionalsAugust 23, 2020Statistical Methods for Sales Forecasting in Retail IndustryMay 24, 2017Incident Duration Prediction – Infrastructure and Real EstateFebruary 27, 2022Load moreRECOMMENDED INSIGHTSAn outlook of healthcare by the year 2040, and how it...How machine learning used in finance and banking?Risk Factors and Predicting Intraoperative, and Postoperative Blood TransfusionRole of big data & analytics in banking and finance -------------------------------------------------------------------------------- /extracted_articles/bctech2146.txt: -------------------------------------------------------------------------------- 1 | Title: Marketing Analytics to Automate Leads Call Status and Reporting - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesMarketing Analytics to Automate Leads Call Status and ReportingOur Success StoriesITMarketing Analytics to Automate Leads Call Status and ReportingByAjay Bidyarthy-August 30, 20212604Client BackgroundClient:A leading Marketing firm in the USAIndustry Type:MarketingServices:Marketing consultingOrganization Size:100+Project ObjectivePrepare a daily report for the companies and upload it to Google Sheets. Data is from callrail and contains all call information about a company.Project DescriptionExtracts data from CallRail database for the last 24 hoursThe data is uploaded to the Google sheet “Call status record”The script runs once a day and is deployed to Heroku by the name “call-status-to-sheets”.The script runs for all companies in the CallRail database.The following data is uploaded:Company NameStatusLocationCustomer NameCall DateCall TimeContact NoCall StatusCall LeadOur SolutionUse CallRail API to get data from database.Run script dailyFilter out excess dataPrepare reportUpload to Google SheetsProject DeliverablesA working deployed automated tool that runs once a day in the morning hours and uploads the data to Google Sheets. Tool is monitored daily.Tools usedHerokuCallRail APIBigQuerySheets APILanguage/techniques usedPythonSkills usedData extraction, cleaning and summarisingDatabases usedGoogle Sheets –   Call status recordWeb Cloud Servers usedHerokuWhat are the technical Challenges Faced during Project ExecutionEnsuring proper amendment of data to sheets without overwriteHow the Technical Challenges were SolvedProper monitoring before final deploymentPrevious articleCallRail, Analytics & Leads Report AlertNext articleMarketing Ads Leads Call Status Data Tool to BigQueryAjay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSCRM (Monday.com, Make.com) to Data Warehouse to Klipfolio DashboardAugust 6, 2023How will COVID-19 affect the world of work?April 29, 2020INDUSTRIAL REVOLUTION 4.0 – PROS AND CONSApril 10, 2020Enhancing Front-End Features and Functionality for Improved User Experience and Dashboard...August 26, 2024Load moreRECOMMENDED INSIGHTSHow to Connect a Domain and Install WordPress on Microsoft AzureAre Customer Analytics Driving Big Data Initiatives?How machine learning will affect your business?Traceability of information – Master your data capital -------------------------------------------------------------------------------- /extracted_articles/bctech2147.txt: -------------------------------------------------------------------------------- 1 | Title: CallRail, Analytics & Leads Report Alert - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesCallRail, Analytics & Leads Report AlertOur Success StoriesITCallRail, Analytics & Leads Report AlertByAjay Bidyarthy-August 30, 20213167Client BackgroundClient:A leading Marketing firm in the USAIndustry Type:MarketingServices:Marketing consultingOrganization Size:100+Project ObjectivePrepare an annual report for the companies and upload it to database. Data is from callrail and contains call analytics.Project DescriptionExtracts data from CallRail database for the last 1 year.The data is uploaded to BigQuery database “lead_report_alert_callrail”The script runs once a year and is deployed to Heroku by the name “lead-report-alert”.Currently, the script is programmed to run for only 2 companies (on a trial basis) – Capital Law Firm and Wilshire Law Firm.The following data is uploaded:Company NameNo. of calls answeredNo. of calls missedNo. of calls abandonedNo. of calls to voicemailTotal CallsOur SolutionUse CallRail API to get data from database.Set time window to be one year.Filter out excess dataPrepare reportUpload to BigQueryProject DeliverablesA working deployed automated tool that runs once a year in the morning hours and uploads the data to BigQuery. Tool is in prototype phase and hence is operational for 2 companies.Tools usedHerokuCallRail APIBigQueryLanguage/techniques usedPythonSkills usedData extraction, cleaning and summarisingDatabases usedBigQuery –  lead_report_alert_callrailWeb Cloud Servers usedHerokuWhat are the technical Challenges Faced during Project ExecutionWorking on a large amount of data since a year’s data contains hundred of thousands of recordsHow the Technical Challenges were SolvedOptimized code for faster processing.Previous articleMarketing Tool to Notify Leads to Clients over Email and PhoneNext articleMarketing Analytics to Automate Leads Call Status and ReportingAjay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSHow to overcome your fear of making mistakes?August 20, 2020What is the difference between Artificial Intelligence, Machine Learning, Statistics, and...March 9, 2021How the COVID-19 crisis is redefining jobs and services?August 15, 2020Impact of AI in health and medicineFebruary 11, 2021Load moreRECOMMENDED INSIGHTSAuvik, Connectwise integration in GrafanaRise of telemedicine and its Impact on Livelihood by 2040Data Engineering and Management tool (Airbyte) with custom data connectors to...How does Metaverse work in the Financial Sector? -------------------------------------------------------------------------------- /extracted_articles/bctech2156.txt: -------------------------------------------------------------------------------- 1 | Title: Budget, Sales KPI Dashboard using Power BI - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesBudget, Sales KPI Dashboard using Power BIOur Success StoriesBanking, Financials, Securities, and InsuranceLifestyle, eCommerce & Online Market PlaceBudget, Sales KPI Dashboard using Power BIByAjay Bidyarthy-July 29, 20214419Project DescriptionWeekly Data – clustered bar chart for weekly Budget & Actual value , weekly Total Budget & Actual value (completed)YTD Data – clustered bar chart for monthly Budget & Actual value , monthly Total Budget & Actual value (completed)Sales History – stacked chart for yearly sales with each month sales , total yearly sale (completed)Dashlet – weekly data – Total weekly Budget , Total weekly Actual , % weekly Budget (completed)Dashlet – YTD data – Total YTD Budget , Total YTD Actual , % YTD Budget (completed)Dashlet – Sales History – Total Sales (completed)Filters – select Area , select City , select Years (completed)Data Visualization DeliverablesPresentationMapDashboardAPI IntegrationData Visualization ToolsKibanaGoogle Data StudioMicrosoft ExcelMicrosoft Power BIData Visualization LanguagesJavaScriptSQLPythonDAXDemoPrevious articleBenefits of Big Data in Different fieldsNext articleELK Stack – Elastic QueriesAjay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSReal life data analysis on stationary and non-stationary Time SeriesFebruary 18, 2019Data security Protect a major enterprise assetJune 12, 2019Driving Insights from the Largest Community for Investors and TradersOctober 8, 2020Efficient Processing and Analysis of Financial Data from PDF Files: Addressing...August 25, 2024Load moreRECOMMENDED INSIGHTSStreamlined Equity Waterfall Calculation and Deal Management SystemA web-based dashboard for the filtered data retrieval of land recordsRising IT Cities and its Impact on the Economy, Environment, Infrastructure,...Transforming Insurance Claim Processing with Automation & Artificial Intelligence -------------------------------------------------------------------------------- /extracted_articles/bctech2157.txt: -------------------------------------------------------------------------------- 1 | Title: Amazon Buy Bot, an Automation AI tool to Auto-Checkouts - Blackcoffer Insights 2 | 3 | HomeOur Success StoriesAmazon Buy Bot, an Automation AI tool to Auto-CheckoutsOur Success StoriesLifestyle, eCommerce & Online Market PlaceAmazon Buy Bot, an Automation AI tool to Auto-CheckoutsByAjay Bidyarthy-June 26, 20213262Client BackgroundClient:A leading consulting firm in the USAIndustry Type:ConsultingServices:Management consultantOrganization Size:100+Project ObjectiveThe main objective of this project is to build the automation tool to buy product on amazon.Project DescriptionThis project is basically completed using selenium and Python. All we have done is write a python script for automation using Selenium.Make some clicks use logics to check item is in stock or not. If the item is in stock then it buys the product otherwise repeat the process again.Our SolutionA simple python code which uses selenium web driver to do all work.Project DeliverablesPython CodeTools usedSelenium WebdriverLanguage/techniques usedPythonSkills usedWeb ScrapingSeleniumProject SnapshotsPrevious articlePredictive Modelling, AI, ML Dashboards in Power BINext articleHow does Big Data Help in Finance and the Growth of Large Firms?Ajay BidyarthyRELATED ARTICLESMORE FROM AUTHORAI and ML-Based YouTube Analytics and Content Creation Tool for Optimizing Subscriber Engagement and Content StrategyEnhancing Front-End Features and Functionality for Improved User Experience and Dashboard Accuracy in Partner Hospital ApplicationROAS Dashboard for Campaign-Wise Google Ads Budget Tracking Using Google Ads APMOST POPULAR INSIGHTSModeling & Simulation for Drug Development & FormulationJanuary 9, 2019ELK Stack – Elastic QueriesAugust 20, 2021NER Task using BERT with data in XML-formatAugust 5, 2023Rising IT Cities and Their Impact on the Economy, Environment, Infrastructure,...August 18, 2023Load moreRECOMMENDED INSIGHTSHow AI will impact the future of work?Sentiment Analysis of a Leading Restaurants Chain in the USAAI Dashboard of Health Fitness – In-Depth LookDo All Social Media Is Owned By Meta? -------------------------------------------------------------------------------- /extracted_articles/desktop.ini: -------------------------------------------------------------------------------- 1 | [.ShellClassInfo] 2 | IconResource=C:\Program Files\Google\Drive File Stream\97.0.1.0\GoogleDriveFS.exe,26 3 | -------------------------------------------------------------------------------- /master dictionary/desktop.ini: -------------------------------------------------------------------------------- 1 | [.ShellClassInfo] 2 | IconResource=C:\Program Files\Google\Drive File Stream\97.0.1.0\GoogleDriveFS.exe,26 3 | -------------------------------------------------------------------------------- /master dictionary/negative-words.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/rubydamodar/ProText-Analyzer/2e4f2b9c4de97aa79f3b48aa4fcf110999b2b89f/master dictionary/negative-words.txt -------------------------------------------------------------------------------- /project Introduction/desktop.ini: -------------------------------------------------------------------------------- 1 | [.ShellClassInfo] 2 | IconResource=C:\Program Files\Google\Drive File Stream\97.0.1.0\GoogleDriveFS.exe,26 3 | -------------------------------------------------------------------------------- /project Introduction/requirement.txt: -------------------------------------------------------------------------------- 1 | pandas==2.0.3 2 | requests==2.31.0 3 | beautifulsoup4==4.12.2 4 | textblob==0.17.1 5 | spacy==3.6.0 6 | syllapy==0.5.0 7 | nltk==3.8.1 8 | openpyxl==3.1.3 -------------------------------------------------------------------------------- /test assignment/desktop.ini: -------------------------------------------------------------------------------- 1 | [.ShellClassInfo] 2 | IconResource=C:\Program Files\Google\Drive File Stream\97.0.1.0\GoogleDriveFS.exe,26 3 | -------------------------------------------------------------------------------- /test assignment/sentiment_analysis.log: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/rubydamodar/ProText-Analyzer/2e4f2b9c4de97aa79f3b48aa4fcf110999b2b89f/test assignment/sentiment_analysis.log -------------------------------------------------------------------------------- /test assignment/textual_analysis_metrics.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/rubydamodar/ProText-Analyzer/2e4f2b9c4de97aa79f3b48aa4fcf110999b2b89f/test assignment/textual_analysis_metrics.xlsx -------------------------------------------------------------------------------- /visualization/word_frequency_visualization.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/rubydamodar/ProText-Analyzer/2e4f2b9c4de97aa79f3b48aa4fcf110999b2b89f/visualization/word_frequency_visualization.png --------------------------------------------------------------------------------