├── LICENSE ├── README.md ├── app ├── app.py └── rag.py ├── data └── data-science-resumes.csv └── screenshots ├── Screenshot 2024-01-17 164527.jpg ├── Screenshot 2024-01-17 164546.jpg ├── Screenshot 2024-01-19 142017.jpg ├── Screenshot 2024-01-19 142532.jpg ├── Screenshot 2024-01-19 142904.jpg ├── Screenshot 2024-01-19 143239.jpg └── Screenshot 2024-01-19 144306.jpg /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2024 Ednalyn C. De Dios 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Resume Database Chatbot Using Local LLM 2 | 3 | > Playing with RAG using Ollama, Langchain, and Streamlit. 4 | 5 | ## Project Description 6 | 7 | This project aims to demonstrate how a recruiter or HR personnel can benefit from a chatbot that answers questions regarding candidates. 8 | 9 | ## Data 10 | 11 | https://www.kaggle.com/datasets/gauravduttakiit/resume-dataset/data 12 | 13 | ## Reference 14 | 15 | https://www.jeremymorgan.com/blog/generative-ai/how-to-run-llm-local-windows/ 16 | https://levelup.gitconnected.com/talk-to-your-csv-llama2-how-to-use-llama2-and-langchain-69012c5ff653 17 | https://blog.duy-huynh.com/build-your-own-rag-and-run-them-locally/ 18 | 19 | https://ollama.ai/library 20 | 21 | ## Usage 22 | 23 | Written in Python 3.9.9. Some technologies used: 24 | 25 | - Ollama 26 | - Lanchain 27 | - Streamlit 28 | 29 | To see the project in action, install the required libraries with 30 | 31 | `pip install langchain langchain-community chromadb fastembed streamlit streamlit_chat ` 32 | 33 | and execute `streamlit run app.py`. 34 | 35 | ## Meta 36 | 37 | Ednalyn C. De Dios – [@ecdedios](https://github.com/ecdedios) 38 | 39 | Distributed under the MIT license. See `LICENSE` for more information. 40 | 41 | - LinkedIn: [in/ecdedios/](https://www.linkedin.com/in/ecdedios/) 42 | - Resumé: [http://ednalyn.com](http://ednalyn.com) 43 | - Data Science Projects [https://datasciencenerd.us](https://datasciencenerd.us) 44 | 45 | ## Contributing 46 | 47 | 1. Fork it () 48 | 2. Create your feature branch (`git checkout -b feature/fooBar`) 49 | 3. Commit your changes (`git commit -am 'Add some fooBar'`) 50 | 4. Push to the branch (`git push origin feature/fooBar`) 51 | 5. Create a new Pull Request 52 | 53 | 2024 54 | -------------------------------------------------------------------------------- /app/app.py: -------------------------------------------------------------------------------- 1 | import os 2 | import tempfile 3 | import streamlit as st 4 | from streamlit_chat import message 5 | from rag import ChatCSV 6 | 7 | # adds a title for the web page 8 | st.set_page_config(page_title="Resume Chatbot") 9 | 10 | def display_messages(): 11 | """ 12 | Displays chat messages in the Streamlit app. 13 | 14 | This function assumes that chat messages are stored in the Streamlit session state 15 | under the key "messages" as a list of tuples, where each tuple contains the message 16 | content and a boolean indicating whether it's a user message or not. 17 | 18 | Additionally, it creates an empty container for a thinking spinner in the Streamlit 19 | session state under the key "thinking_spinner". 20 | 21 | Note: Streamlit (st) functions are used for displaying content in a Streamlit app. 22 | """ 23 | # Display a subheader for the chat. 24 | st.subheader("Chat") 25 | 26 | # Iterate through messages stored in the session state. 27 | for i, (msg, is_user) in enumerate(st.session_state["messages"]): 28 | # Display each message using the message function with appropriate styling. 29 | message(msg, is_user=is_user, key=str(i)) 30 | 31 | # Create an empty container for a thinking spinner and store it in the session state. 32 | st.session_state["thinking_spinner"] = st.empty() 33 | 34 | def process_input(): 35 | """ 36 | Processes user input and updates the chat messages in the Streamlit app. 37 | 38 | This function assumes that user input is stored in the Streamlit session state 39 | under the key "user_input," and the question-answering assistant is stored 40 | under the key "assistant." 41 | 42 | Additionally, it utilizes Streamlit functions for displaying a thinking spinner 43 | and updating the chat messages. 44 | 45 | Note: Streamlit (st) functions are used for interacting with the Streamlit app. 46 | """ 47 | # Check if there is user input and it is not empty. 48 | if st.session_state["user_input"] and len(st.session_state["user_input"].strip()) > 0: 49 | # Extract and clean the user input. 50 | user_text = st.session_state["user_input"].strip() 51 | 52 | # Display a thinking spinner while the assistant processes the input. 53 | with st.session_state["thinking_spinner"], st.spinner(f"Thinking"): 54 | # Ask the assistant for a response based on the user input. 55 | agent_text = st.session_state["assistant"].ask(user_text) 56 | 57 | # Append user and assistant messages to the chat messages in the session state. 58 | st.session_state["messages"].append((user_text, True)) 59 | st.session_state["messages"].append((agent_text, False)) 60 | 61 | def read_and_save_file(): 62 | """ 63 | Reads and saves the uploaded file, performs ingestion, and clears the assistant state. 64 | 65 | This function assumes that the question-answering assistant is stored in the Streamlit 66 | session state under the key "assistant," and file-related information is stored under 67 | the key "file_uploader." 68 | 69 | Additionally, it utilizes Streamlit functions for displaying spinners and updating the 70 | assistant's state. 71 | 72 | Note: Streamlit (st) functions are used for interacting with the Streamlit app. 73 | """ 74 | # Clear the state of the question-answering assistant. 75 | st.session_state["assistant"].clear() 76 | 77 | # Clear the chat messages and user input in the session state. 78 | st.session_state["messages"] = [] 79 | st.session_state["user_input"] = "" 80 | 81 | # Iterate through the uploaded files in the session state. 82 | for file in st.session_state["file_uploader"]: 83 | # Save the file to a temporary location and get the file path. 84 | with tempfile.NamedTemporaryFile(delete=False) as tf: 85 | tf.write(file.getbuffer()) 86 | file_path = tf.name 87 | 88 | # Display a spinner while ingesting the file. 89 | with st.session_state["ingestion_spinner"], st.spinner(f"Ingesting {file.name}"): 90 | st.session_state["assistant"].ingest(file_path) 91 | os.remove(file_path) 92 | 93 | 94 | def page(): 95 | """ 96 | Defines the content of the Streamlit app page for ChatCSV. 97 | 98 | This function sets up the initial session state if it doesn't exist and displays 99 | the main components of the Streamlit app, including the header, file uploader, 100 | and associated functionalities. 101 | 102 | Note: Streamlit (st) functions are used for interacting with the Streamlit app. 103 | """ 104 | # Check if the session state is empty (first time loading the app). 105 | if len(st.session_state) == 0: 106 | # Initialize the session state with empty chat messages and a ChatCSV assistant. 107 | st.session_state["messages"] = [] 108 | st.session_state["assistant"] = ChatCSV() 109 | 110 | # Display the main header of the Streamlit app. 111 | st.header("ChatCSV") 112 | 113 | # Display a subheader and a file uploader for uploading CSV files. 114 | st.subheader("Upload a csv file") 115 | st.file_uploader( 116 | "Upload csv", 117 | type=["csv"], 118 | key="file_uploader", 119 | on_change=read_and_save_file, 120 | label_visibility="collapsed", 121 | accept_multiple_files=True, 122 | ) 123 | 124 | # Create an empty container for a spinner related to file ingestion 125 | # and store it in the Streamlit session state under the key "ingestion_spinner". 126 | st.session_state["ingestion_spinner"] = st.empty() 127 | 128 | # Display chat messages in the Streamlit app using the defined function. 129 | display_messages() 130 | 131 | # Display a text input field for user messages in the Streamlit app. 132 | # The input field has a key "user_input," and the on_change event triggers the 133 | # "process_input" function when the input changes. 134 | st.text_input("Message", key="user_input", on_change=process_input) 135 | 136 | # Check if the script is being run as the main module. 137 | if __name__ == "__main__": 138 | # Call the "page" function to set up and run the Streamlit app. 139 | page() -------------------------------------------------------------------------------- /app/rag.py: -------------------------------------------------------------------------------- 1 | from langchain_community.vectorstores import Chroma 2 | from langchain_community.chat_models import ChatOllama 3 | from langchain_community.embeddings import FastEmbedEmbeddings 4 | from langchain.schema.output_parser import StrOutputParser 5 | from langchain_community.document_loaders.csv_loader import CSVLoader 6 | from langchain.text_splitter import RecursiveCharacterTextSplitter 7 | from langchain.schema.runnable import RunnablePassthrough 8 | from langchain.prompts import PromptTemplate 9 | from langchain.vectorstores.utils import filter_complex_metadata 10 | 11 | class ChatCSV: 12 | vector_store = None 13 | retriever = None 14 | chain = None 15 | 16 | def __init__(self): 17 | """ 18 | Initializes the question-answering system with default configurations. 19 | 20 | This constructor sets up the following components: 21 | - A ChatOllama model for generating responses ('neural-chat'). 22 | - A RecursiveCharacterTextSplitter for splitting text into chunks. 23 | - A PromptTemplate for constructing prompts with placeholders for question and context. 24 | """ 25 | # Initialize the ChatOllama model with 'neural-chat'. 26 | self.model = ChatOllama(model="neural-chat") 27 | 28 | # Initialize the RecursiveCharacterTextSplitter with specific chunk settings. 29 | self.text_splitter = RecursiveCharacterTextSplitter(chunk_size=1024, chunk_overlap=100) 30 | 31 | # Initialize the PromptTemplate with a predefined template for constructing prompts. 32 | self.prompt = PromptTemplate.from_template( 33 | """ 34 | [INST] You are a helpful HR assistant that analyses resumes from different candidates. 35 | Use the following pieces of retrieved context to answer the question. 36 | Give names when possible. If you don't know the answer, 37 | just say that you don't know. [/INST] 38 | [INST] Question: {question} 39 | Context: {context} 40 | Answer: [/INST] 41 | """ 42 | ) 43 | 44 | def ingest(self, csv_file_path: str): 45 | ''' 46 | Ingests data from a CSV file containing resumes, process the data, and set up the 47 | components for further analysis. 48 | 49 | Parameters: 50 | - csv_file_path (str): The file path to the CSV file. 51 | 52 | Usage: 53 | obj.ingest("/path/to/data.csv") 54 | 55 | This function uses a CSVLoader to load the data from the specified CSV file. 56 | 57 | Args: 58 | - file.path (str): The path to the CSV file. 59 | - encoding (str): The character encoding of the file (default is 'utf-8'). 60 | - source_column (str): The column in the CSV containing the data (default is "Resume"). 61 | ''' 62 | loader = CSVLoader( 63 | file_path=csv_file_path, 64 | encoding='utf-8', 65 | source_column="Resume" 66 | ) 67 | 68 | # loads the data 69 | data = loader.load() 70 | 71 | # splits the documents into chunks 72 | chunks = self.text_splitter.split_documents(data) 73 | chunks = filter_complex_metadata(chunks) 74 | 75 | # creates a vector store using embedding 76 | vector_store = Chroma.from_documents(documents=chunks, embedding=FastEmbedEmbeddings()) 77 | # sets up the retriever 78 | self.retriever = vector_store.as_retriever( 79 | search_type="similarity_score_threshold", 80 | search_kwargs={ 81 | "k": 3, 82 | "score_threshold": 0.5, 83 | }, 84 | ) 85 | 86 | # Define a processing chain for handling a question-answer scenario. 87 | # The chain consists of the following components: 88 | # 1. "context" from the retriever 89 | # 2. A passthrough for the "question" 90 | # 3. Processing with the "prompt" 91 | # 4. Interaction with the "model" 92 | # 5. Parsing the output using the "StrOutputParser" 93 | self.chain = ({"context": self.retriever, "question": RunnablePassthrough()} 94 | | self.prompt 95 | | self.model 96 | | StrOutputParser()) 97 | 98 | def ask(self, query: str): 99 | """ 100 | Asks a question using the configured processing chain. 101 | 102 | Parameters: 103 | - query (str): The question to be asked. 104 | 105 | Returns: 106 | - str: The result of processing the question through the configured chain. 107 | If the processing chain is not set up (empty), a message is returned 108 | prompting to add a CSV document first. 109 | """ 110 | if not self.chain: 111 | return "Please, add a CSV document first." 112 | 113 | return self.chain.invoke(query) 114 | 115 | def clear(self): 116 | """ 117 | Clears the components in the question-answering system. 118 | 119 | This method resets the vector store, retriever, and processing chain to None, 120 | effectively clearing the existing configuration. 121 | """ 122 | # Set the vector store to None. 123 | self.vector_store = None 124 | 125 | # Set the retriever to None. 126 | self.retriever = None 127 | 128 | # Set the processing chain to None. 129 | self.chain = None -------------------------------------------------------------------------------- /data/data-science-resumes.csv: -------------------------------------------------------------------------------- 1 | Candidate ID,Resume 2 | C0001,"Skills * Programming Languages: Python (pandas, numpy, scipy, scikit-learn, matplotlib), Sql, Java, JavaScript/JQuery. * Machine learning: Regression, SVM, Naïve Bayes, KNN, Random Forest, Decision Trees, Boosting techniques, Cluster Analysis, Word Embedding, Sentiment Analysis, Natural Language processing, Dimensionality reduction, Topic Modelling (LDA, NMF), PCA & Neural Nets. * Database Visualizations: Mysql, SqlServer, Cassandra, Hbase, ElasticSearch D3.js, DC.js, Plotly, kibana, matplotlib, ggplot, Tableau. * Others: Regular Expression, HTML, CSS, Angular 6, Logstash, Kafka, Python Flask, Git, Docker, computer vision - Open CV and understanding of Deep learning.Education Details 3 | 4 | Data Science Assurance Associate 5 | 6 | Data Science Assurance Associate - Ernst & Young LLP 7 | Skill Details 8 | JAVASCRIPT- Exprience - 24 months 9 | jQuery- Exprience - 24 months 10 | Python- Exprience - 24 monthsCompany Details 11 | company - Ernst & Young LLP 12 | description - Fraud Investigations and Dispute Services Assurance 13 | TECHNOLOGY ASSISTED REVIEW 14 | TAR (Technology Assisted Review) assists in accelerating the review process and run analytics and generate reports. 15 | * Core member of a team helped in developing automated review platform tool from scratch for assisting E discovery domain, this tool implements predictive coding and topic modelling by automating reviews, resulting in reduced labor costs and time spent during the lawyers review. 16 | * Understand the end to end flow of the solution, doing research and development for classification models, predictive analysis and mining of the information present in text data. Worked on analyzing the outputs and precision monitoring for the entire tool. 17 | * TAR assists in predictive coding, topic modelling from the evidence by following EY standards. Developed the classifier models in order to identify ""red flags"" and fraud-related issues. 18 | 19 | Tools & Technologies: Python, scikit-learn, tfidf, word2vec, doc2vec, cosine similarity, Naïve Bayes, LDA, NMF for topic modelling, Vader and text blob for sentiment analysis. Matplot lib, Tableau dashboard for reporting. 20 | 21 | MULTIPLE DATA SCIENCE AND ANALYTIC PROJECTS (USA CLIENTS) 22 | TEXT ANALYTICS - MOTOR VEHICLE CUSTOMER REVIEW DATA * Received customer feedback survey data for past one year. Performed sentiment (Positive, Negative & Neutral) and time series analysis on customer comments across all 4 categories. 23 | * Created heat map of terms by survey category based on frequency of words * Extracted Positive and Negative words across all the Survey categories and plotted Word cloud. 24 | * Created customized tableau dashboards for effective reporting and visualizations. 25 | CHATBOT * Developed a user friendly chatbot for one of our Products which handle simple questions about hours of operation, reservation options and so on. 26 | * This chat bot serves entire product related questions. Giving overview of tool via QA platform and also give recommendation responses so that user question to build chain of relevant answer. 27 | * This too has intelligence to build the pipeline of questions as per user requirement and asks the relevant /recommended questions. 28 | 29 | Tools & Technologies: Python, Natural language processing, NLTK, spacy, topic modelling, Sentiment analysis, Word Embedding, scikit-learn, JavaScript/JQuery, SqlServer 30 | 31 | INFORMATION GOVERNANCE 32 | Organizations to make informed decisions about all of the information they store. The integrated Information Governance portfolio synthesizes intelligence across unstructured data sources and facilitates action to ensure organizations are best positioned to counter information risk. 33 | * Scan data from multiple sources of formats and parse different file formats, extract Meta data information, push results for indexing elastic search and created customized, interactive dashboards using kibana. 34 | * Preforming ROT Analysis on the data which give information of data which helps identify content that is either Redundant, Outdated, or Trivial. 35 | * Preforming full-text search analysis on elastic search with predefined methods which can tag as (PII) personally identifiable information (social security numbers, addresses, names, etc.) which frequently targeted during cyber-attacks. 36 | Tools & Technologies: Python, Flask, Elastic Search, Kibana 37 | 38 | FRAUD ANALYTIC PLATFORM 39 | Fraud Analytics and investigative platform to review all red flag cases. 40 | • FAP is a Fraud Analytics and investigative platform with inbuilt case manager and suite of Analytics for various ERP systems. 41 | * It can be used by clients to interrogate their Accounting systems for identifying the anomalies which can be indicators of fraud by running advanced analytics 42 | Tools & Technologies: HTML, JavaScript, SqlServer, JQuery, CSS, Bootstrap, Node.js, D3.js, DC.js" 43 | C0002,"Education Details 44 | May 2013 to May 2017 B.E UIT-RGPV 45 | Data Scientist 46 | 47 | Data Scientist - Matelabs 48 | Skill Details 49 | Python- Exprience - Less than 1 year months 50 | Statsmodels- Exprience - 12 months 51 | AWS- Exprience - Less than 1 year months 52 | Machine learning- Exprience - Less than 1 year months 53 | Sklearn- Exprience - Less than 1 year months 54 | Scipy- Exprience - Less than 1 year months 55 | Keras- Exprience - Less than 1 year monthsCompany Details 56 | company - Matelabs 57 | description - ML Platform for business professionals, dummies and enthusiasts. 58 | 60/A Koramangala 5th block, 59 | Achievements/Tasks behind sukh sagar, Bengaluru, 60 | India Developed and deployed auto preprocessing steps of machine learning mainly missing value 61 | treatment, outlier detection, encoding, scaling, feature selection and dimensionality reduction. 62 | Deployed automated classification and regression model. 63 | linkedin.com/in/aditya-rathore- 64 | b4600b146 Reasearch and deployed the time series forecasting model ARIMA, SARIMAX, Holt-winter and 65 | Prophet. 66 | Worked on meta-feature extracting problem. 67 | github.com/rathorology 68 | Implemented a state of the art research paper on outlier detection for mixed attributes. 69 | company - Matelabs 70 | description - " 71 | C0003,"Areas of Interest Deep Learning, Control System Design, Programming in-Python, Electric Machinery, Web Development, Analytics Technical Activities q Hindustan Aeronautics Limited, Bangalore - For 4 weeks under the guidance of Mr. Satish, Senior Engineer in the hangar of Mirage 2000 fighter aircraft Technical Skills Programming Matlab, Python and Java, LabView, Python WebFrameWork-Django, Flask, LTSPICE-intermediate Languages and and MIPOWER-intermediate, Github (GitBash), Jupyter Notebook, Xampp, MySQL-Basics, Python Software Packages Interpreters-Anaconda, Python2, Python3, Pycharm, Java IDE-Eclipse Operating Systems Windows, Ubuntu, Debian-Kali Linux Education Details 72 | January 2019 B.Tech. Electrical and Electronics Engineering Manipal Institute of Technology 73 | January 2015 DEEKSHA CENTER 74 | January 2013 Little Flower Public School 75 | August 2000 Manipal Academy of Higher 76 | DATA SCIENCE 77 | 78 | DATA SCIENCE AND ELECTRICAL ENTHUSIAST 79 | Skill Details 80 | Data Analysis- Exprience - Less than 1 year months 81 | excel- Exprience - Less than 1 year months 82 | Machine Learning- Exprience - Less than 1 year months 83 | mathematics- Exprience - Less than 1 year months 84 | Python- Exprience - Less than 1 year months 85 | Matlab- Exprience - Less than 1 year months 86 | Electrical Engineering- Exprience - Less than 1 year months 87 | Sql- Exprience - Less than 1 year monthsCompany Details 88 | company - THEMATHCOMPANY 89 | description - I am currently working with a Casino based operator(name not to be disclosed) in Macau.I need to segment the customers who visit their property based on the value the patrons bring into the company.Basically prove that the segmentation can be done in much better way than the current system which they have with proper numbers to back it up.Henceforth they can implement target marketing strategy to attract their customers who add value to the business." 90 | C0004,"Skills • R • Python • SAP HANA • Tableau • SAP HANA SQL • SAP HANA PAL • MS SQL • SAP Lumira • C# • Linear Programming • Data Modelling • Advance Analytics • SCM Analytics • Retail Analytics •Social Media Analytics • NLP Education Details 91 | January 2017 to January 2018 PGDM Business Analytics Great Lakes Institute of Management & Illinois Institute of Technology 92 | January 2013 Bachelor of Engineering Electronics and Communication Bengaluru, Karnataka New Horizon College of Engineering, Bangalore Visvesvaraya Technological University 93 | Data Science Consultant 94 | 95 | Consultant - Deloitte USI 96 | Skill Details 97 | LINEAR PROGRAMMING- Exprience - 6 months 98 | RETAIL- Exprience - 6 months 99 | RETAIL MARKETING- Exprience - 6 months 100 | SCM- Exprience - 6 months 101 | SQL- Exprience - Less than 1 year months 102 | Deep Learning- Exprience - Less than 1 year months 103 | Machine learning- Exprience - Less than 1 year months 104 | Python- Exprience - Less than 1 year months 105 | R- Exprience - Less than 1 year monthsCompany Details 106 | company - Deloitte USI 107 | description - The project involved analysing historic deals and coming with insights to optimize future deals. 108 | Role: Was given raw data, carried out end to end analysis and presented insights to client. 109 | Key Responsibilities: 110 | • Extract data from client systems across geographies. 111 | • Understand and build reports in tableau. Infer meaningful insights to optimize prices and find out process blockades. 112 | Technical Environment: R, Tableau. 113 | 114 | Industry: Cross Industry 115 | Service Area: Cross Industry - Products 116 | Project Name: Handwriting recognition 117 | Consultant: 3 months. 118 | The project involved taking handwritten images and converting them to digital text images by object detection and sentence creation. 119 | Role: I was developing sentence correction functionality. 120 | Key Responsibilities: 121 | • Gather data large enough to capture all English words 122 | • Train LSTM models on words. 123 | Technical Environment: Python. 124 | 125 | Industry: Finance 126 | Service Area: Financial Services - BI development Project Name: SWIFT 127 | Consultant: 8 months. 128 | The project was to develop an analytics infrastructure on top of SAP S/4, it would user to view 129 | financial reports to respective departments. Reporting also included forecasting expenses. 130 | Role: I was leading the offshore team. 131 | Key Responsibilities: 132 | • Design & Develop data models for reporting. 133 | • Develop ETL for data flow 134 | • Validate various reports. 135 | Technical Environment: SAP HANA, Tableau, SAP AO. 136 | 137 | Industry: Healthcare Analytics 138 | Service Area: Life Sciences - Product development Project Name: Clinical Healthcare System 139 | Consultant: 2 months. 140 | The project was to develop an analytics infrastructure on top of Argus, it would allow users to query faster and provide advance analytics capabilities. 141 | Role: I was involved from design to deploy phase, performed a lot of data restructuring and built 142 | models for insights. 143 | Key Responsibilities: 144 | • Design & Develop data models for reporting. 145 | • Develop and deploy analytical models. 146 | • Validate various reports. 147 | Technical Environment: Data Modelling, SAP HANA, Tableau, NLP. 148 | 149 | Industry: FMCG 150 | Service Area: Trade & Promotion 151 | Project Name: Consumption Based Planning for Flowers Foods Consultant; 8 months. 152 | The project involved setting up of CRM and CBP modules. 153 | Role: I was involved in key data decomposition activities and setting up the base for future year 154 | forecast. Over the course of the project I developed various models and carried out key 155 | performance improvements. 156 | Key Responsibilities: 157 | • Design & Develop HANA models for decomposition. 158 | • Develop data flow for forecast. 159 | • Developed various views for reporting of Customer/Sales/Funds. 160 | • Validate various reports in BOBJ. 161 | Technical Environment: Data Modelling, SAP HANA, BOBJ, Time Series Forecasting. 162 | 163 | Internal Initiative Industry: FMCG 164 | Customer Segmentation and RFM analysis Consultant; 3 months. 165 | The initiative involved setting up of HANA-Python interface and advance analytics on Python. Over the course I had successfully segmented data into five core segments using K-means and carried out RFM analysis in Python. Also developed algorithm to categorize any new customer under the defined buckets. 166 | Technical Environment: Anaconda3, Python3.6, HANA SPS12 167 | 168 | Industry: Telecom Invoice state detection Consultant; 1 months. 169 | The initiative was to reduce the manual effort in verifying closed and open invoices manually, it 170 | involved development to a decision tree to classify open/closed invoices. This enabled effort 171 | reduction by 60%. 172 | Technical Environment: R, SAP PAL, SAP HANA SPS12 173 | 174 | Accenture Experience 175 | Industry: Analytics - Cross Industry 176 | In Process Analytics for SAP Senior Developer; 19 months. 177 | Accenture Solutions Pvt. Ltd., India 178 | The project involved development of SAP analytics tool - In Process Analytics (IPA) . My role was to develop database objects and data models to provide operational insights to clients. 179 | Role: I have developed various Finance related KPIs and spearheaded various deployments. 180 | Introduced SAP Predictive analytics to reduce development time and reuse functionalities for KPIs and prepared production planning reports. 181 | Key Responsibilities: 182 | • Involved in information gather phase. 183 | • Designed and implemented SAP HANA data modelling using Attribute View, Analytic View, and 184 | Calculation View. 185 | • Developed various KPI's individually using complex SQL scripts in Calculation views. 186 | • Created procedures in HANA Database. 187 | • Took ownership and developed Dashboard functionality. 188 | • Involved in building data processing algorithms to be executed in R server for cluster analysis. 189 | Technical Environment: R, SAP HANA, T-SQL. 190 | Industry: Cross Industry 191 | Accenture Testing Accelerator for SAP Database Developer; 21 months. 192 | Accenture Solutions Pvt. Ltd., India 193 | Role: I have taken care of all development activities for the ATAS tool and have also completed 194 | various deployments of the product. 195 | Apart from these activities I was also actively involved in maintenance of the database servers 196 | (Production & Quality) 197 | Key Responsibilities: 198 | • Analyzing business requirements, understanding the scope, getting requirements clarified 199 | interacting with business and further transform all requirements to generate attribute 200 | mapping documents and reviewing mapping specification documentation 201 | • Create / Update database objects like tables, views, stored procedures, function, and packages 202 | • Monitored SQL Server Error Logs and Application Logs through SQL Server Agent 203 | • Prepared Data Flow Diagrams, Entity Relationship Diagrams using UML 204 | • Responsible for Designing, developing and Normalization of database tables 205 | • Experience in performance tuning using SQL profiler. 206 | • Involved in QA, UAT, knowledge transfer and support activities 207 | Technical Environment: SQL Server 2008/2014, Visual Studio 2010, Windows Server, Performance 208 | Monitor, SQL Server Profiler, C#, PL-SQL, T-SQL." 209 | C0005,"Education Details 210 | MCA YMCAUST, Faridabad, Haryana 211 | Data Science internship 212 | 213 | 214 | Skill Details 215 | Data Structure- Exprience - Less than 1 year months 216 | C- Exprience - Less than 1 year months 217 | Data Analysis- Exprience - Less than 1 year months 218 | Python- Exprience - Less than 1 year months 219 | Core Java- Exprience - Less than 1 year months 220 | Database Management- Exprience - Less than 1 year monthsCompany Details 221 | company - Itechpower 222 | description - " 223 | C0006,"SKILLS C Basics, IOT, Python, MATLAB, Data Science, Machine Learning, HTML, Microsoft Word, Microsoft Excel, Microsoft Powerpoint. RECOGNITION Academic Secured First place in B.Tech.Education Details 224 | August 2014 to May 2018 B.Tech. Ghatkesar, Andhra Pradesh Aurora's Scientific and Technological Institute 225 | June 2012 to May 2014 Secondary Education Warangal, Telangana SR Junior College 226 | Data Science 227 | 228 | 229 | Skill Details 230 | MS OFFICE- Exprience - Less than 1 year months 231 | C- Exprience - Less than 1 year months 232 | machine learning- Exprience - Less than 1 year months 233 | data science- Exprience - Less than 1 year months 234 | Matlab- Exprience - Less than 1 year monthsCompany Details 235 | company - 236 | description - " 237 | C0007,"Skills • Python • Tableau • Data Visualization • R Studio • Machine Learning • Statistics IABAC Certified Data Scientist with versatile experience over 1+ years in managing business, data science consulting and leading innovation projects, bringing business ideas to working real world solutions. Being a strong advocator of augmented era, where human capabilities are enhanced by machines, Fahed is passionate about bringing business concepts in area of machine learning, AI, robotics etc., to real life solutions.Education Details 238 | January 2017 B. Tech Computer Science & Engineering Mohali, Punjab Indo Global College of Engineering 239 | Data Science Consultant 240 | 241 | Data Science Consultant - Datamites 242 | Skill Details 243 | MACHINE LEARNING- Exprience - 13 months 244 | PYTHON- Exprience - 24 months 245 | SOLUTIONS- Exprience - 24 months 246 | DATA SCIENCE- Exprience - 24 months 247 | DATA VISUALIZATION- Exprience - 24 months 248 | Tableau- Exprience - 24 monthsCompany Details 249 | company - Datamites 250 | description - • Analyzed and processed complex data sets using advanced querying, visualization and analytics tools. 251 | • Responsible for loading, extracting and validation of client data. 252 | • Worked on manipulating, cleaning & processing data using python. 253 | • Used Tableau for data visualization. 254 | company - Heretic Solutions Pvt Ltd 255 | description - • Worked closely with business to identify issues and used data to propose solutions for effective decision making. 256 | • Manipulating, cleansing & processing data using Python, Excel and R. 257 | • Analyzed raw data, drawing conclusions & developing recommendations. 258 | • Used machine learning tools and statistical techniques to produce solutions to problems." 259 | C0008,"Education Details 260 | B.Tech Rayat and Bahra Institute of Engineering and Biotechnology 261 | Data Science 262 | 263 | Data Science 264 | Skill Details 265 | Numpy- Exprience - Less than 1 year months 266 | Machine Learning- Exprience - Less than 1 year months 267 | Tensorflow- Exprience - Less than 1 year months 268 | Scikit- Exprience - Less than 1 year months 269 | Python- Exprience - Less than 1 year months 270 | GCP- Exprience - Less than 1 year months 271 | Pandas- Exprience - Less than 1 year months 272 | Neural Network- Exprience - Less than 1 year monthsCompany Details 273 | company - Wipro 274 | description - Bhawana Aggarwal 275 | E-Mail:bhawana.chd@gmail.com 276 | Phone: 09876971076 277 | VVersatile, high-energy professional targeting challenging assignments in Machine 278 | PROFILE SUMMARY 279 | ▪ An IT professional with knowledge and experience of 2 years in Wipro Technologies in Machine 280 | Learning, Deep Learning, Data Science, Python, Software Development. 281 | ▪ Skilled in managing end-to-end development and software products / projects from inception, requirement 282 | specs, planning, designing, implementation, configuration and documentation. 283 | ▪ Knowledge on Python , Machine Learning, Deep Learning, data Science, Algorithms, Neural Network, 284 | NLP, GCP. 285 | ▪ Knowledge on Python Libraries like Numpy, Pandas, Seaborn , Matplotlib, Cufflinks. 286 | ▪ Knowledge on different algorithms in Machine learning like KNN, Decision Tree, Bias variance Trade off, 287 | Support vector Machine(SVM),Logistic Regression, Neural networks. 288 | ▪ Have knowledge on unsupervised, Supervised and reinforcement data. 289 | ▪ Programming experience in relational platforms like MySQL,Oracle. 290 | ▪ Have knowledge on Some programming language like C++,Java. 291 | ▪ Experience in cloud based environment like Google Cloud. 292 | ▪ Working on different Operating System like Linux, Ubuntu, Windows. 293 | ▪ Good interpersonal and communication skills. 294 | ▪ Problem solving skills with the ability to think laterally, and to think with a medium term and long term 295 | perspective 296 | ▪ Flexibility and an open attitude to change. 297 | ▪ Ability to create, define and own frameworks with a strong emphasis on code reusability. 298 | TECHNICAL SKILLS 299 | Programming Languages Python, C 300 | Libraries Seaborn, Numpy, Pandas, Cufflinks, Matplotlib 301 | Algorithms 302 | KNN, Decision Tree, Linear regression, Logistic Regression, Neural Networks, K means clustering, 303 | Tensorflow, SVM 304 | Databases SQL, Oracle 305 | Operating Systems Linux, Window 306 | Development Environments NetBeans, Notebooks, Sublime 307 | Ticketing tools Service Now, Remedy 308 | Education 309 | UG Education: 310 | B.Tech (Computer Science) from Rayat and Bahra Institute of Engineering and Biotechnology passed with 78.4%in 311 | 2016. 312 | Schooling: 313 | XII in 2012 from Moti Ram Arya Sr. Secondary School(Passed with 78.4%) 314 | X in 2010 from Valley Public School (Passed with 9.4 CGPA) 315 | WORK EXPERINCE 316 | Title : Wipro Neural Intelligence Platform 317 | Team Size : 5 318 | Brief: Wipro’s Neural Intelligence Platform harnesses the power of automation and artificial intelligence 319 | technologies—natural language processing (NLP), cognitive, machine learning, and analytics. The platform 320 | comprises three layers: a data engagement platform that can easily access and manage multiple structured and 321 | unstructured data sources; an “intent assessment and reasoning” engine that includes sentiment and predictive 322 | analytics; and a deep machine learning engine that can sense, act, and learn over time. The project entailed 323 | automating responses to user queries at the earliest. The Monster Bot using the power of Deep Machine Learning, 324 | NLP to handle such queries. User can see the how their queries can be answered quickly like allL1 activities can be 325 | eliminated. 326 | Entity Extractor -> This involves text extraction and NLP for fetching out important information from the text like 327 | dates, names, places, contact numbers etc. This involves Regex, Bluemix NLU api’s and machine learning using 328 | Tensor flow for further learning of new entities. 329 | Classifier ->This involves the classifications of classes, training of dataset and predicting the output using the SKLearn 330 | classifier (MNB, SVM, SGD as Classifier) and SGD for the optimization to map the user queries with the best 331 | suited response and make the system efficient. 332 | NER: A Deep Learning NER Model is trained to extract the entities from the text. Entities like Roles, Skills, 333 | Organizations can be extracted from raw text. RNN(LSTM) Bidirectional model is trained for extracting such entities 334 | using Keras TensorFlow framework. 335 | OTHER PROJECTS 336 | Title : Diabetes Detection 337 | Brief : Developed the software which can detect whether the person is suffering from Diabetes or not and got the third 338 | prize in it. 339 | TRAINING AND CERTIFICATIONS 340 | Title: Python Training, Machine Learning, Data Science, Deep Learning 341 | Organization: Udemy, Coursera (Machine Learning, Deep Learning) 342 | Personal Profile 343 | Father’s Name :Mr. Tirlok Aggarwal 344 | Language Known : English & Hindi 345 | Marital Status :Single 346 | Date of Birth(Gender):1993-12-20(YYYY-MM-DD) (F) 347 | company - Wipro 348 | description - Developing programs in Python. 349 | company - Wipro 350 | description - Title : Wipro Neural Intelligence Platform 351 | Team Size : 5 352 | Brief: Wipro’s Neural Intelligence Platform harnesses the power of automation and artificial intelligence 353 | technologies—natural language processing (NLP), cognitive, machine learning, and analytics. The platform 354 | comprises three layers: a data engagement platform that can easily access and manage multiple structured and 355 | unstructured data sources; an “intent assessment and reasoning” engine that includes sentiment and predictive 356 | analytics; and a deep machine learning engine that can sense, act, and learn over time. The project entailed 357 | automating responses to user queries at the earliest. The Monster Bot using the power of Deep Machine Learning, 358 | NLP to handle such queries. User can see the how their queries can be answered quickly like allL1 activities can be 359 | eliminated. 360 | Entity Extractor -> This involves text extraction and NLP for fetching out important information from the text like 361 | dates, names, places, contact numbers etc. This involves Regex, Bluemix NLU api’s and machine learning using 362 | Tensor flow for further learning of new entities. 363 | Classifier ->This involves the classifications of classes, training of dataset and predicting the output using the SKLearn 364 | classifier (MNB, SVM, SGD as Classifier) and SGD for the optimization to map the user queries with the best 365 | suited response and make the system efficient. 366 | NER: A Deep Learning NER Model is trained to extract the entities from the text. Entities like Roles, Skills, 367 | Organizations can be extracted from raw text. RNN(LSTM) Bidirectional model is trained for extracting such entities 368 | using Keras TensorFlow framework. 369 | company - Wipro Technologies 370 | description - An IT professional with knowledge and experience of 2 years in Wipro Technologies in Machine 371 | Learning, Deep Learning, Data Science, Python, Software Development. 372 | ▪ Skilled in managing end-to-end development and software products / projects from inception, requirement 373 | specs, planning, designing, implementation, configuration and documentation. 374 | ▪ Knowledge on Python , Machine Learning, Deep Learning, data Science, Algorithms, Neural Network, 375 | NLP, GCP. 376 | ▪ Knowledge on Python Libraries like Numpy, Pandas, Seaborn , Matplotlib, Cufflinks. 377 | ▪ Knowledge on different algorithms in Machine learning like KNN, Decision Tree, Bias variance Trade off, 378 | Support vector Machine(SVM),Logistic Regression, Neural networks. 379 | ▪ Have knowledge on unsupervised, Supervised and reinforcement data. 380 | ▪ Programming experience in relational platforms like MySQL,Oracle. 381 | ▪ Have knowledge on Some programming language like C++,Java. 382 | ▪ Experience in cloud based environment like Google Cloud. 383 | ▪ Working on different Operating System like Linux, Ubuntu, Windows. 384 | ▪ Good interpersonal and communication skills. 385 | ▪ Problem solving skills with the ability to think laterally, and to think with a medium term and long term 386 | perspective 387 | ▪ Flexibility and an open attitude to change. 388 | ▪ Ability to create, define and own frameworks with a strong emphasis on code reusability." 389 | C0009,"Personal Skills ➢ Ability to quickly grasp technical aspects and willingness to learn ➢ High energy levels & Result oriented. Education Details 390 | January 2018 Master of Engineering Computer Technology & Application Bhopal, Madhya Pradesh Truba Institute of Engineering & Information Technology 391 | January 2010 B.E. computer science Bhopal, Madhya Pradesh RKDF Institute of Science and Technology College of Engineering 392 | January 2006 Polytechnic Information Technology Vidisha, Madhya Pradesh SATI Engineering College in Vidisha 393 | January 2003 M.tech Thesis Detail BMCH School in Ganj basoda 394 | Data science 395 | 396 | I have six month experience in Data Science. Key Skills: - Experience in Machine Learning, Deep Leaning, NLP, Python, SQL, Web Scraping Good knowledge in computer subjects and ability to update 397 | Skill Details 398 | Experience in Machine Learning, Deep Learning, NLP, Python, SQL, Web Crawling, HTML,CSS.- Exprience - Less than 1 year monthsCompany Details 399 | company - RNT.AI Technology Solution 400 | description - Text classification using Machine learning Algorithms with python. 401 | Practical knowledge of Deep learning algorithms such as  Recurrent Neural Networks(RNN). 402 | Develop custom data models and algorithms to apply to dataset 403 | Experience with Python packages like Pandas, Scikit-learn, Tensor Flow, Numpy, Matplotliv, NLTK. 404 | Comfort with SQL,  MYSQL 405 | Sentiment analysis. 406 |  Apply leave Dataset using classification technique like Tf--idf , LSA with cosine similarity using Machine learning Algorithms. 407 | Web crawling using Selenium web driver and Beautiful Soup with python. 408 | company - Life Insurance Corporation of India Bhopal 409 | description - ü Explaining policy features and the benefits 410 | ü Updated knowledge of life insurance products and shared with customers" 411 | C0010,"Expertise − Data and Quantitative Analysis − Decision Analytics − Predictive Modeling − Data-Driven Personalization − KPI Dashboards − Big Data Queries and Interpretation − Data Mining and Visualization Tools − Machine Learning Algorithms − Business Intelligence (BI) − Research, Reports and Forecasts Education Details 412 | PGP in Data Science Mumbai, Maharashtra Aegis School of data science & Business 413 | B.E. in Electronics & Communication Electronics & Communication Indore, Madhya Pradesh IES IPS Academy 414 | Data Scientist 415 | 416 | Data Scientist with PR Canada 417 | Skill Details 418 | Algorithms- Exprience - 6 months 419 | BI- Exprience - 6 months 420 | Business Intelligence- Exprience - 6 months 421 | Machine Learning- Exprience - 24 months 422 | Visualization- Exprience - 24 months 423 | spark- Exprience - 24 months 424 | python- Exprience - 36 months 425 | tableau- Exprience - 36 months 426 | Data Analysis- Exprience - 24 monthsCompany Details 427 | company - Aegis school of Data Science & Business 428 | description - Mostly working on industry project for providing solution along with Teaching Appointments: Teach undergraduate and graduate-level courses in Spark and Machine Learning as an adjunct faculty member at Aegis School of Data Science, Mumbai (2017 to Present) 429 | company - Aegis school of Data & Business 430 | description - Data Science Intern, Nov 2015 to Jan 2016 431 | 432 | Furnish executive leadership team with insights, analytics, reports and recommendations enabling effective strategic planning across all business units, distribution channels and product lines. 433 | 434 | ➔ Chat Bot using AWS LEX and Tensor flow Python 435 | The goal of project creates a chat bot for an academic institution or university to handle queries related courses offered by that institute. The objective of this task is to reduce human efforts as well as reduce man made errors. Even by this companies handle their client 24x7. In this case companies are academic institutions and clients are participants or students. 436 | ➔ Web scraping using Selenium web driver Python 437 | The task is to scrap the data from the online messaging portal in a text format and have to find the pattern form it. 438 | ➔ Data Visualization and Data insights Hadoop Eco System, Hive, PySpark, QlikSense 439 | The goal of this project is to build a Business Solutions to a Internet Service Provider Company, like handling data which is generated per day basis, for that we have to visualize that data and find the usage pattern form it and have a generate a reports. 440 | ➔ Image Based Fraud Detection Microsoft Face API, PySpark, Open CV 441 | The main goal of project is Recognize similarity for a face to given Database images. Face recognition is the recognizing a special face from set of different faces. Face is extracted and then compared with the database Image if that Image recognized then the person already applied for loan from somewhere else and now hiding his or her identity, this is how we are going to prevent the frauds in the initial stage itself. 442 | ➔ Churn Analysis for Internet Service Provider R, Python, Machine Learning, Hadoop 443 | The objective is to identify the customer who is likely to churn in a given period of time; we have to pretend the customer giving incentive offers. 444 | ➔ Sentiment Analysis Python, NLP, Apache Spark service in IBM Bluemix. 445 | This project is highly emphasis on tweets from Twitter data were taken for mobile networks service provider to do a sentiment analysis and analyze whether the expressed opinion was positive, negative or neutral, capture the emotions of the tweets and comparative analysis. 446 | 447 | Quantifiable Results: 448 | − Mentored 7-12 Data Science Enthusiast each year that have all since gone on to graduate school in Data Science and Business Analytics. 449 | − Reviewed and evaluated 20-40 Research Papers on Data Science for one of the largest Data Science Conference called Data Science Congress by Aegis School of Business Mumbai. 450 | − Heading a solution providing organization called Data Science Delivered into Aegis school of Data Science Mumbai and managed 4-5 live projects using Data Science techniques. 451 | − Working for some social cause with the help of Data Science for Social Goods Committee, where our team developed a product called ""Let's find a missing Child"" for helping society. 452 | company - IBM India pvt ltd 453 | description - Mostly worked on blumix and IBM Watson for Data science." 454 | C0011,"Skills * Programming Languages: Python (pandas, numpy, scipy, scikit-learn, matplotlib), Sql, Java, JavaScript/JQuery. * Machine learning: Regression, SVM, Naïve Bayes, KNN, Random Forest, Decision Trees, Boosting techniques, Cluster Analysis, Word Embedding, Sentiment Analysis, Natural Language processing, Dimensionality reduction, Topic Modelling (LDA, NMF), PCA & Neural Nets. * Database Visualizations: Mysql, SqlServer, Cassandra, Hbase, ElasticSearch D3.js, DC.js, Plotly, kibana, matplotlib, ggplot, Tableau. * Others: Regular Expression, HTML, CSS, Angular 6, Logstash, Kafka, Python Flask, Git, Docker, computer vision - Open CV and understanding of Deep learning.Education Details 455 | 456 | Data Science Assurance Associate 457 | 458 | Data Science Assurance Associate - Ernst & Young LLP 459 | Skill Details 460 | JAVASCRIPT- Exprience - 24 months 461 | jQuery- Exprience - 24 months 462 | Python- Exprience - 24 monthsCompany Details 463 | company - Ernst & Young LLP 464 | description - Fraud Investigations and Dispute Services Assurance 465 | TECHNOLOGY ASSISTED REVIEW 466 | TAR (Technology Assisted Review) assists in accelerating the review process and run analytics and generate reports. 467 | * Core member of a team helped in developing automated review platform tool from scratch for assisting E discovery domain, this tool implements predictive coding and topic modelling by automating reviews, resulting in reduced labor costs and time spent during the lawyers review. 468 | * Understand the end to end flow of the solution, doing research and development for classification models, predictive analysis and mining of the information present in text data. Worked on analyzing the outputs and precision monitoring for the entire tool. 469 | * TAR assists in predictive coding, topic modelling from the evidence by following EY standards. Developed the classifier models in order to identify ""red flags"" and fraud-related issues. 470 | 471 | Tools & Technologies: Python, scikit-learn, tfidf, word2vec, doc2vec, cosine similarity, Naïve Bayes, LDA, NMF for topic modelling, Vader and text blob for sentiment analysis. Matplot lib, Tableau dashboard for reporting. 472 | 473 | MULTIPLE DATA SCIENCE AND ANALYTIC PROJECTS (USA CLIENTS) 474 | TEXT ANALYTICS - MOTOR VEHICLE CUSTOMER REVIEW DATA * Received customer feedback survey data for past one year. Performed sentiment (Positive, Negative & Neutral) and time series analysis on customer comments across all 4 categories. 475 | * Created heat map of terms by survey category based on frequency of words * Extracted Positive and Negative words across all the Survey categories and plotted Word cloud. 476 | * Created customized tableau dashboards for effective reporting and visualizations. 477 | CHATBOT * Developed a user friendly chatbot for one of our Products which handle simple questions about hours of operation, reservation options and so on. 478 | * This chat bot serves entire product related questions. Giving overview of tool via QA platform and also give recommendation responses so that user question to build chain of relevant answer. 479 | * This too has intelligence to build the pipeline of questions as per user requirement and asks the relevant /recommended questions. 480 | 481 | Tools & Technologies: Python, Natural language processing, NLTK, spacy, topic modelling, Sentiment analysis, Word Embedding, scikit-learn, JavaScript/JQuery, SqlServer 482 | 483 | INFORMATION GOVERNANCE 484 | Organizations to make informed decisions about all of the information they store. The integrated Information Governance portfolio synthesizes intelligence across unstructured data sources and facilitates action to ensure organizations are best positioned to counter information risk. 485 | * Scan data from multiple sources of formats and parse different file formats, extract Meta data information, push results for indexing elastic search and created customized, interactive dashboards using kibana. 486 | * Preforming ROT Analysis on the data which give information of data which helps identify content that is either Redundant, Outdated, or Trivial. 487 | * Preforming full-text search analysis on elastic search with predefined methods which can tag as (PII) personally identifiable information (social security numbers, addresses, names, etc.) which frequently targeted during cyber-attacks. 488 | Tools & Technologies: Python, Flask, Elastic Search, Kibana 489 | 490 | FRAUD ANALYTIC PLATFORM 491 | Fraud Analytics and investigative platform to review all red flag cases. 492 | • FAP is a Fraud Analytics and investigative platform with inbuilt case manager and suite of Analytics for various ERP systems. 493 | * It can be used by clients to interrogate their Accounting systems for identifying the anomalies which can be indicators of fraud by running advanced analytics 494 | Tools & Technologies: HTML, JavaScript, SqlServer, JQuery, CSS, Bootstrap, Node.js, D3.js, DC.js" 495 | C0012,"Education Details 496 | May 2013 to May 2017 B.E UIT-RGPV 497 | Data Scientist 498 | 499 | Data Scientist - Matelabs 500 | Skill Details 501 | Python- Exprience - Less than 1 year months 502 | Statsmodels- Exprience - 12 months 503 | AWS- Exprience - Less than 1 year months 504 | Machine learning- Exprience - Less than 1 year months 505 | Sklearn- Exprience - Less than 1 year months 506 | Scipy- Exprience - Less than 1 year months 507 | Keras- Exprience - Less than 1 year monthsCompany Details 508 | company - Matelabs 509 | description - ML Platform for business professionals, dummies and enthusiasts. 510 | 60/A Koramangala 5th block, 511 | Achievements/Tasks behind sukh sagar, Bengaluru, 512 | India Developed and deployed auto preprocessing steps of machine learning mainly missing value 513 | treatment, outlier detection, encoding, scaling, feature selection and dimensionality reduction. 514 | Deployed automated classification and regression model. 515 | linkedin.com/in/aditya-rathore- 516 | b4600b146 Reasearch and deployed the time series forecasting model ARIMA, SARIMAX, Holt-winter and 517 | Prophet. 518 | Worked on meta-feature extracting problem. 519 | github.com/rathorology 520 | Implemented a state of the art research paper on outlier detection for mixed attributes. 521 | company - Matelabs 522 | description - " 523 | C0013,"Areas of Interest Deep Learning, Control System Design, Programming in-Python, Electric Machinery, Web Development, Analytics Technical Activities q Hindustan Aeronautics Limited, Bangalore - For 4 weeks under the guidance of Mr. Satish, Senior Engineer in the hangar of Mirage 2000 fighter aircraft Technical Skills Programming Matlab, Python and Java, LabView, Python WebFrameWork-Django, Flask, LTSPICE-intermediate Languages and and MIPOWER-intermediate, Github (GitBash), Jupyter Notebook, Xampp, MySQL-Basics, Python Software Packages Interpreters-Anaconda, Python2, Python3, Pycharm, Java IDE-Eclipse Operating Systems Windows, Ubuntu, Debian-Kali Linux Education Details 524 | January 2019 B.Tech. Electrical and Electronics Engineering Manipal Institute of Technology 525 | January 2015 DEEKSHA CENTER 526 | January 2013 Little Flower Public School 527 | August 2000 Manipal Academy of Higher 528 | DATA SCIENCE 529 | 530 | DATA SCIENCE AND ELECTRICAL ENTHUSIAST 531 | Skill Details 532 | Data Analysis- Exprience - Less than 1 year months 533 | excel- Exprience - Less than 1 year months 534 | Machine Learning- Exprience - Less than 1 year months 535 | mathematics- Exprience - Less than 1 year months 536 | Python- Exprience - Less than 1 year months 537 | Matlab- Exprience - Less than 1 year months 538 | Electrical Engineering- Exprience - Less than 1 year months 539 | Sql- Exprience - Less than 1 year monthsCompany Details 540 | company - THEMATHCOMPANY 541 | description - I am currently working with a Casino based operator(name not to be disclosed) in Macau.I need to segment the customers who visit their property based on the value the patrons bring into the company.Basically prove that the segmentation can be done in much better way than the current system which they have with proper numbers to back it up.Henceforth they can implement target marketing strategy to attract their customers who add value to the business." 542 | C0014,"Skills • R • Python • SAP HANA • Tableau • SAP HANA SQL • SAP HANA PAL • MS SQL • SAP Lumira • C# • Linear Programming • Data Modelling • Advance Analytics • SCM Analytics • Retail Analytics •Social Media Analytics • NLP Education Details 543 | January 2017 to January 2018 PGDM Business Analytics Great Lakes Institute of Management & Illinois Institute of Technology 544 | January 2013 Bachelor of Engineering Electronics and Communication Bengaluru, Karnataka New Horizon College of Engineering, Bangalore Visvesvaraya Technological University 545 | Data Science Consultant 546 | 547 | Consultant - Deloitte USI 548 | Skill Details 549 | LINEAR PROGRAMMING- Exprience - 6 months 550 | RETAIL- Exprience - 6 months 551 | RETAIL MARKETING- Exprience - 6 months 552 | SCM- Exprience - 6 months 553 | SQL- Exprience - Less than 1 year months 554 | Deep Learning- Exprience - Less than 1 year months 555 | Machine learning- Exprience - Less than 1 year months 556 | Python- Exprience - Less than 1 year months 557 | R- Exprience - Less than 1 year monthsCompany Details 558 | company - Deloitte USI 559 | description - The project involved analysing historic deals and coming with insights to optimize future deals. 560 | Role: Was given raw data, carried out end to end analysis and presented insights to client. 561 | Key Responsibilities: 562 | • Extract data from client systems across geographies. 563 | • Understand and build reports in tableau. Infer meaningful insights to optimize prices and find out process blockades. 564 | Technical Environment: R, Tableau. 565 | 566 | Industry: Cross Industry 567 | Service Area: Cross Industry - Products 568 | Project Name: Handwriting recognition 569 | Consultant: 3 months. 570 | The project involved taking handwritten images and converting them to digital text images by object detection and sentence creation. 571 | Role: I was developing sentence correction functionality. 572 | Key Responsibilities: 573 | • Gather data large enough to capture all English words 574 | • Train LSTM models on words. 575 | Technical Environment: Python. 576 | 577 | Industry: Finance 578 | Service Area: Financial Services - BI development Project Name: SWIFT 579 | Consultant: 8 months. 580 | The project was to develop an analytics infrastructure on top of SAP S/4, it would user to view 581 | financial reports to respective departments. Reporting also included forecasting expenses. 582 | Role: I was leading the offshore team. 583 | Key Responsibilities: 584 | • Design & Develop data models for reporting. 585 | • Develop ETL for data flow 586 | • Validate various reports. 587 | Technical Environment: SAP HANA, Tableau, SAP AO. 588 | 589 | Industry: Healthcare Analytics 590 | Service Area: Life Sciences - Product development Project Name: Clinical Healthcare System 591 | Consultant: 2 months. 592 | The project was to develop an analytics infrastructure on top of Argus, it would allow users to query faster and provide advance analytics capabilities. 593 | Role: I was involved from design to deploy phase, performed a lot of data restructuring and built 594 | models for insights. 595 | Key Responsibilities: 596 | • Design & Develop data models for reporting. 597 | • Develop and deploy analytical models. 598 | • Validate various reports. 599 | Technical Environment: Data Modelling, SAP HANA, Tableau, NLP. 600 | 601 | Industry: FMCG 602 | Service Area: Trade & Promotion 603 | Project Name: Consumption Based Planning for Flowers Foods Consultant; 8 months. 604 | The project involved setting up of CRM and CBP modules. 605 | Role: I was involved in key data decomposition activities and setting up the base for future year 606 | forecast. Over the course of the project I developed various models and carried out key 607 | performance improvements. 608 | Key Responsibilities: 609 | • Design & Develop HANA models for decomposition. 610 | • Develop data flow for forecast. 611 | • Developed various views for reporting of Customer/Sales/Funds. 612 | • Validate various reports in BOBJ. 613 | Technical Environment: Data Modelling, SAP HANA, BOBJ, Time Series Forecasting. 614 | 615 | Internal Initiative Industry: FMCG 616 | Customer Segmentation and RFM analysis Consultant; 3 months. 617 | The initiative involved setting up of HANA-Python interface and advance analytics on Python. Over the course I had successfully segmented data into five core segments using K-means and carried out RFM analysis in Python. Also developed algorithm to categorize any new customer under the defined buckets. 618 | Technical Environment: Anaconda3, Python3.6, HANA SPS12 619 | 620 | Industry: Telecom Invoice state detection Consultant; 1 months. 621 | The initiative was to reduce the manual effort in verifying closed and open invoices manually, it 622 | involved development to a decision tree to classify open/closed invoices. This enabled effort 623 | reduction by 60%. 624 | Technical Environment: R, SAP PAL, SAP HANA SPS12 625 | 626 | Accenture Experience 627 | Industry: Analytics - Cross Industry 628 | In Process Analytics for SAP Senior Developer; 19 months. 629 | Accenture Solutions Pvt. Ltd., India 630 | The project involved development of SAP analytics tool - In Process Analytics (IPA) . My role was to develop database objects and data models to provide operational insights to clients. 631 | Role: I have developed various Finance related KPIs and spearheaded various deployments. 632 | Introduced SAP Predictive analytics to reduce development time and reuse functionalities for KPIs and prepared production planning reports. 633 | Key Responsibilities: 634 | • Involved in information gather phase. 635 | • Designed and implemented SAP HANA data modelling using Attribute View, Analytic View, and 636 | Calculation View. 637 | • Developed various KPI's individually using complex SQL scripts in Calculation views. 638 | • Created procedures in HANA Database. 639 | • Took ownership and developed Dashboard functionality. 640 | • Involved in building data processing algorithms to be executed in R server for cluster analysis. 641 | Technical Environment: R, SAP HANA, T-SQL. 642 | Industry: Cross Industry 643 | Accenture Testing Accelerator for SAP Database Developer; 21 months. 644 | Accenture Solutions Pvt. Ltd., India 645 | Role: I have taken care of all development activities for the ATAS tool and have also completed 646 | various deployments of the product. 647 | Apart from these activities I was also actively involved in maintenance of the database servers 648 | (Production & Quality) 649 | Key Responsibilities: 650 | • Analyzing business requirements, understanding the scope, getting requirements clarified 651 | interacting with business and further transform all requirements to generate attribute 652 | mapping documents and reviewing mapping specification documentation 653 | • Create / Update database objects like tables, views, stored procedures, function, and packages 654 | • Monitored SQL Server Error Logs and Application Logs through SQL Server Agent 655 | • Prepared Data Flow Diagrams, Entity Relationship Diagrams using UML 656 | • Responsible for Designing, developing and Normalization of database tables 657 | • Experience in performance tuning using SQL profiler. 658 | • Involved in QA, UAT, knowledge transfer and support activities 659 | Technical Environment: SQL Server 2008/2014, Visual Studio 2010, Windows Server, Performance 660 | Monitor, SQL Server Profiler, C#, PL-SQL, T-SQL." 661 | C0015,"Education Details 662 | MCA YMCAUST, Faridabad, Haryana 663 | Data Science internship 664 | 665 | 666 | Skill Details 667 | Data Structure- Exprience - Less than 1 year months 668 | C- Exprience - Less than 1 year months 669 | Data Analysis- Exprience - Less than 1 year months 670 | Python- Exprience - Less than 1 year months 671 | Core Java- Exprience - Less than 1 year months 672 | Database Management- Exprience - Less than 1 year monthsCompany Details 673 | company - Itechpower 674 | description - " 675 | C0016,"SKILLS C Basics, IOT, Python, MATLAB, Data Science, Machine Learning, HTML, Microsoft Word, Microsoft Excel, Microsoft Powerpoint. RECOGNITION Academic Secured First place in B.Tech.Education Details 676 | August 2014 to May 2018 B.Tech. Ghatkesar, Andhra Pradesh Aurora's Scientific and Technological Institute 677 | June 2012 to May 2014 Secondary Education Warangal, Telangana SR Junior College 678 | Data Science 679 | 680 | 681 | Skill Details 682 | MS OFFICE- Exprience - Less than 1 year months 683 | C- Exprience - Less than 1 year months 684 | machine learning- Exprience - Less than 1 year months 685 | data science- Exprience - Less than 1 year months 686 | Matlab- Exprience - Less than 1 year monthsCompany Details 687 | company - 688 | description - " 689 | C0017,"Skills • Python • Tableau • Data Visualization • R Studio • Machine Learning • Statistics IABAC Certified Data Scientist with versatile experience over 1+ years in managing business, data science consulting and leading innovation projects, bringing business ideas to working real world solutions. Being a strong advocator of augmented era, where human capabilities are enhanced by machines, Fahed is passionate about bringing business concepts in area of machine learning, AI, robotics etc., to real life solutions.Education Details 690 | January 2017 B. Tech Computer Science & Engineering Mohali, Punjab Indo Global College of Engineering 691 | Data Science Consultant 692 | 693 | Data Science Consultant - Datamites 694 | Skill Details 695 | MACHINE LEARNING- Exprience - 13 months 696 | PYTHON- Exprience - 24 months 697 | SOLUTIONS- Exprience - 24 months 698 | DATA SCIENCE- Exprience - 24 months 699 | DATA VISUALIZATION- Exprience - 24 months 700 | Tableau- Exprience - 24 monthsCompany Details 701 | company - Datamites 702 | description - • Analyzed and processed complex data sets using advanced querying, visualization and analytics tools. 703 | • Responsible for loading, extracting and validation of client data. 704 | • Worked on manipulating, cleaning & processing data using python. 705 | • Used Tableau for data visualization. 706 | company - Heretic Solutions Pvt Ltd 707 | description - • Worked closely with business to identify issues and used data to propose solutions for effective decision making. 708 | • Manipulating, cleansing & processing data using Python, Excel and R. 709 | • Analyzed raw data, drawing conclusions & developing recommendations. 710 | • Used machine learning tools and statistical techniques to produce solutions to problems." 711 | C0018,"Education Details 712 | B.Tech Rayat and Bahra Institute of Engineering and Biotechnology 713 | Data Science 714 | 715 | Data Science 716 | Skill Details 717 | Numpy- Exprience - Less than 1 year months 718 | Machine Learning- Exprience - Less than 1 year months 719 | Tensorflow- Exprience - Less than 1 year months 720 | Scikit- Exprience - Less than 1 year months 721 | Python- Exprience - Less than 1 year months 722 | GCP- Exprience - Less than 1 year months 723 | Pandas- Exprience - Less than 1 year months 724 | Neural Network- Exprience - Less than 1 year monthsCompany Details 725 | company - Wipro 726 | description - Bhawana Aggarwal 727 | E-Mail:bhawana.chd@gmail.com 728 | Phone: 09876971076 729 | VVersatile, high-energy professional targeting challenging assignments in Machine 730 | PROFILE SUMMARY 731 | ▪ An IT professional with knowledge and experience of 2 years in Wipro Technologies in Machine 732 | Learning, Deep Learning, Data Science, Python, Software Development. 733 | ▪ Skilled in managing end-to-end development and software products / projects from inception, requirement 734 | specs, planning, designing, implementation, configuration and documentation. 735 | ▪ Knowledge on Python , Machine Learning, Deep Learning, data Science, Algorithms, Neural Network, 736 | NLP, GCP. 737 | ▪ Knowledge on Python Libraries like Numpy, Pandas, Seaborn , Matplotlib, Cufflinks. 738 | ▪ Knowledge on different algorithms in Machine learning like KNN, Decision Tree, Bias variance Trade off, 739 | Support vector Machine(SVM),Logistic Regression, Neural networks. 740 | ▪ Have knowledge on unsupervised, Supervised and reinforcement data. 741 | ▪ Programming experience in relational platforms like MySQL,Oracle. 742 | ▪ Have knowledge on Some programming language like C++,Java. 743 | ▪ Experience in cloud based environment like Google Cloud. 744 | ▪ Working on different Operating System like Linux, Ubuntu, Windows. 745 | ▪ Good interpersonal and communication skills. 746 | ▪ Problem solving skills with the ability to think laterally, and to think with a medium term and long term 747 | perspective 748 | ▪ Flexibility and an open attitude to change. 749 | ▪ Ability to create, define and own frameworks with a strong emphasis on code reusability. 750 | TECHNICAL SKILLS 751 | Programming Languages Python, C 752 | Libraries Seaborn, Numpy, Pandas, Cufflinks, Matplotlib 753 | Algorithms 754 | KNN, Decision Tree, Linear regression, Logistic Regression, Neural Networks, K means clustering, 755 | Tensorflow, SVM 756 | Databases SQL, Oracle 757 | Operating Systems Linux, Window 758 | Development Environments NetBeans, Notebooks, Sublime 759 | Ticketing tools Service Now, Remedy 760 | Education 761 | UG Education: 762 | B.Tech (Computer Science) from Rayat and Bahra Institute of Engineering and Biotechnology passed with 78.4%in 763 | 2016. 764 | Schooling: 765 | XII in 2012 from Moti Ram Arya Sr. Secondary School(Passed with 78.4%) 766 | X in 2010 from Valley Public School (Passed with 9.4 CGPA) 767 | WORK EXPERINCE 768 | Title : Wipro Neural Intelligence Platform 769 | Team Size : 5 770 | Brief: Wipro’s Neural Intelligence Platform harnesses the power of automation and artificial intelligence 771 | technologies—natural language processing (NLP), cognitive, machine learning, and analytics. The platform 772 | comprises three layers: a data engagement platform that can easily access and manage multiple structured and 773 | unstructured data sources; an “intent assessment and reasoning” engine that includes sentiment and predictive 774 | analytics; and a deep machine learning engine that can sense, act, and learn over time. The project entailed 775 | automating responses to user queries at the earliest. The Monster Bot using the power of Deep Machine Learning, 776 | NLP to handle such queries. User can see the how their queries can be answered quickly like allL1 activities can be 777 | eliminated. 778 | Entity Extractor -> This involves text extraction and NLP for fetching out important information from the text like 779 | dates, names, places, contact numbers etc. This involves Regex, Bluemix NLU api’s and machine learning using 780 | Tensor flow for further learning of new entities. 781 | Classifier ->This involves the classifications of classes, training of dataset and predicting the output using the SKLearn 782 | classifier (MNB, SVM, SGD as Classifier) and SGD for the optimization to map the user queries with the best 783 | suited response and make the system efficient. 784 | NER: A Deep Learning NER Model is trained to extract the entities from the text. Entities like Roles, Skills, 785 | Organizations can be extracted from raw text. RNN(LSTM) Bidirectional model is trained for extracting such entities 786 | using Keras TensorFlow framework. 787 | OTHER PROJECTS 788 | Title : Diabetes Detection 789 | Brief : Developed the software which can detect whether the person is suffering from Diabetes or not and got the third 790 | prize in it. 791 | TRAINING AND CERTIFICATIONS 792 | Title: Python Training, Machine Learning, Data Science, Deep Learning 793 | Organization: Udemy, Coursera (Machine Learning, Deep Learning) 794 | Personal Profile 795 | Father’s Name :Mr. Tirlok Aggarwal 796 | Language Known : English & Hindi 797 | Marital Status :Single 798 | Date of Birth(Gender):1993-12-20(YYYY-MM-DD) (F) 799 | company - Wipro 800 | description - Developing programs in Python. 801 | company - Wipro 802 | description - Title : Wipro Neural Intelligence Platform 803 | Team Size : 5 804 | Brief: Wipro’s Neural Intelligence Platform harnesses the power of automation and artificial intelligence 805 | technologies—natural language processing (NLP), cognitive, machine learning, and analytics. The platform 806 | comprises three layers: a data engagement platform that can easily access and manage multiple structured and 807 | unstructured data sources; an “intent assessment and reasoning” engine that includes sentiment and predictive 808 | analytics; and a deep machine learning engine that can sense, act, and learn over time. The project entailed 809 | automating responses to user queries at the earliest. The Monster Bot using the power of Deep Machine Learning, 810 | NLP to handle such queries. User can see the how their queries can be answered quickly like allL1 activities can be 811 | eliminated. 812 | Entity Extractor -> This involves text extraction and NLP for fetching out important information from the text like 813 | dates, names, places, contact numbers etc. This involves Regex, Bluemix NLU api’s and machine learning using 814 | Tensor flow for further learning of new entities. 815 | Classifier ->This involves the classifications of classes, training of dataset and predicting the output using the SKLearn 816 | classifier (MNB, SVM, SGD as Classifier) and SGD for the optimization to map the user queries with the best 817 | suited response and make the system efficient. 818 | NER: A Deep Learning NER Model is trained to extract the entities from the text. Entities like Roles, Skills, 819 | Organizations can be extracted from raw text. RNN(LSTM) Bidirectional model is trained for extracting such entities 820 | using Keras TensorFlow framework. 821 | company - Wipro Technologies 822 | description - An IT professional with knowledge and experience of 2 years in Wipro Technologies in Machine 823 | Learning, Deep Learning, Data Science, Python, Software Development. 824 | ▪ Skilled in managing end-to-end development and software products / projects from inception, requirement 825 | specs, planning, designing, implementation, configuration and documentation. 826 | ▪ Knowledge on Python , Machine Learning, Deep Learning, data Science, Algorithms, Neural Network, 827 | NLP, GCP. 828 | ▪ Knowledge on Python Libraries like Numpy, Pandas, Seaborn , Matplotlib, Cufflinks. 829 | ▪ Knowledge on different algorithms in Machine learning like KNN, Decision Tree, Bias variance Trade off, 830 | Support vector Machine(SVM),Logistic Regression, Neural networks. 831 | ▪ Have knowledge on unsupervised, Supervised and reinforcement data. 832 | ▪ Programming experience in relational platforms like MySQL,Oracle. 833 | ▪ Have knowledge on Some programming language like C++,Java. 834 | ▪ Experience in cloud based environment like Google Cloud. 835 | ▪ Working on different Operating System like Linux, Ubuntu, Windows. 836 | ▪ Good interpersonal and communication skills. 837 | ▪ Problem solving skills with the ability to think laterally, and to think with a medium term and long term 838 | perspective 839 | ▪ Flexibility and an open attitude to change. 840 | ▪ Ability to create, define and own frameworks with a strong emphasis on code reusability." 841 | C0019,"Personal Skills ➢ Ability to quickly grasp technical aspects and willingness to learn ➢ High energy levels & Result oriented. Education Details 842 | January 2018 Master of Engineering Computer Technology & Application Bhopal, Madhya Pradesh Truba Institute of Engineering & Information Technology 843 | January 2010 B.E. computer science Bhopal, Madhya Pradesh RKDF Institute of Science and Technology College of Engineering 844 | January 2006 Polytechnic Information Technology Vidisha, Madhya Pradesh SATI Engineering College in Vidisha 845 | January 2003 M.tech Thesis Detail BMCH School in Ganj basoda 846 | Data science 847 | 848 | I have six month experience in Data Science. Key Skills: - Experience in Machine Learning, Deep Leaning, NLP, Python, SQL, Web Scraping Good knowledge in computer subjects and ability to update 849 | Skill Details 850 | Experience in Machine Learning, Deep Learning, NLP, Python, SQL, Web Crawling, HTML,CSS.- Exprience - Less than 1 year monthsCompany Details 851 | company - RNT.AI Technology Solution 852 | description - Text classification using Machine learning Algorithms with python. 853 | Practical knowledge of Deep learning algorithms such as  Recurrent Neural Networks(RNN). 854 | Develop custom data models and algorithms to apply to dataset 855 | Experience with Python packages like Pandas, Scikit-learn, Tensor Flow, Numpy, Matplotliv, NLTK. 856 | Comfort with SQL,  MYSQL 857 | Sentiment analysis. 858 |  Apply leave Dataset using classification technique like Tf--idf , LSA with cosine similarity using Machine learning Algorithms. 859 | Web crawling using Selenium web driver and Beautiful Soup with python. 860 | company - Life Insurance Corporation of India Bhopal 861 | description - ü Explaining policy features and the benefits 862 | ü Updated knowledge of life insurance products and shared with customers" 863 | C0020,"Expertise − Data and Quantitative Analysis − Decision Analytics − Predictive Modeling − Data-Driven Personalization − KPI Dashboards − Big Data Queries and Interpretation − Data Mining and Visualization Tools − Machine Learning Algorithms − Business Intelligence (BI) − Research, Reports and Forecasts Education Details 864 | PGP in Data Science Mumbai, Maharashtra Aegis School of data science & Business 865 | B.E. in Electronics & Communication Electronics & Communication Indore, Madhya Pradesh IES IPS Academy 866 | Data Scientist 867 | 868 | Data Scientist with PR Canada 869 | Skill Details 870 | Algorithms- Exprience - 6 months 871 | BI- Exprience - 6 months 872 | Business Intelligence- Exprience - 6 months 873 | Machine Learning- Exprience - 24 months 874 | Visualization- Exprience - 24 months 875 | spark- Exprience - 24 months 876 | python- Exprience - 36 months 877 | tableau- Exprience - 36 months 878 | Data Analysis- Exprience - 24 monthsCompany Details 879 | company - Aegis school of Data Science & Business 880 | description - Mostly working on industry project for providing solution along with Teaching Appointments: Teach undergraduate and graduate-level courses in Spark and Machine Learning as an adjunct faculty member at Aegis School of Data Science, Mumbai (2017 to Present) 881 | company - Aegis school of Data & Business 882 | description - Data Science Intern, Nov 2015 to Jan 2016 883 | 884 | Furnish executive leadership team with insights, analytics, reports and recommendations enabling effective strategic planning across all business units, distribution channels and product lines. 885 | 886 | ➔ Chat Bot using AWS LEX and Tensor flow Python 887 | The goal of project creates a chat bot for an academic institution or university to handle queries related courses offered by that institute. The objective of this task is to reduce human efforts as well as reduce man made errors. Even by this companies handle their client 24x7. In this case companies are academic institutions and clients are participants or students. 888 | ➔ Web scraping using Selenium web driver Python 889 | The task is to scrap the data from the online messaging portal in a text format and have to find the pattern form it. 890 | ➔ Data Visualization and Data insights Hadoop Eco System, Hive, PySpark, QlikSense 891 | The goal of this project is to build a Business Solutions to a Internet Service Provider Company, like handling data which is generated per day basis, for that we have to visualize that data and find the usage pattern form it and have a generate a reports. 892 | ➔ Image Based Fraud Detection Microsoft Face API, PySpark, Open CV 893 | The main goal of project is Recognize similarity for a face to given Database images. Face recognition is the recognizing a special face from set of different faces. Face is extracted and then compared with the database Image if that Image recognized then the person already applied for loan from somewhere else and now hiding his or her identity, this is how we are going to prevent the frauds in the initial stage itself. 894 | ➔ Churn Analysis for Internet Service Provider R, Python, Machine Learning, Hadoop 895 | The objective is to identify the customer who is likely to churn in a given period of time; we have to pretend the customer giving incentive offers. 896 | ➔ Sentiment Analysis Python, NLP, Apache Spark service in IBM Bluemix. 897 | This project is highly emphasis on tweets from Twitter data were taken for mobile networks service provider to do a sentiment analysis and analyze whether the expressed opinion was positive, negative or neutral, capture the emotions of the tweets and comparative analysis. 898 | 899 | Quantifiable Results: 900 | − Mentored 7-12 Data Science Enthusiast each year that have all since gone on to graduate school in Data Science and Business Analytics. 901 | − Reviewed and evaluated 20-40 Research Papers on Data Science for one of the largest Data Science Conference called Data Science Congress by Aegis School of Business Mumbai. 902 | − Heading a solution providing organization called Data Science Delivered into Aegis school of Data Science Mumbai and managed 4-5 live projects using Data Science techniques. 903 | − Working for some social cause with the help of Data Science for Social Goods Committee, where our team developed a product called ""Let's find a missing Child"" for helping society. 904 | company - IBM India pvt ltd 905 | description - Mostly worked on blumix and IBM Watson for Data science." 906 | C0021,"Skills * Programming Languages: Python (pandas, numpy, scipy, scikit-learn, matplotlib), Sql, Java, JavaScript/JQuery. * Machine learning: Regression, SVM, Naïve Bayes, KNN, Random Forest, Decision Trees, Boosting techniques, Cluster Analysis, Word Embedding, Sentiment Analysis, Natural Language processing, Dimensionality reduction, Topic Modelling (LDA, NMF), PCA & Neural Nets. * Database Visualizations: Mysql, SqlServer, Cassandra, Hbase, ElasticSearch D3.js, DC.js, Plotly, kibana, matplotlib, ggplot, Tableau. * Others: Regular Expression, HTML, CSS, Angular 6, Logstash, Kafka, Python Flask, Git, Docker, computer vision - Open CV and understanding of Deep learning.Education Details 907 | 908 | Data Science Assurance Associate 909 | 910 | Data Science Assurance Associate - Ernst & Young LLP 911 | Skill Details 912 | JAVASCRIPT- Exprience - 24 months 913 | jQuery- Exprience - 24 months 914 | Python- Exprience - 24 monthsCompany Details 915 | company - Ernst & Young LLP 916 | description - Fraud Investigations and Dispute Services Assurance 917 | TECHNOLOGY ASSISTED REVIEW 918 | TAR (Technology Assisted Review) assists in accelerating the review process and run analytics and generate reports. 919 | * Core member of a team helped in developing automated review platform tool from scratch for assisting E discovery domain, this tool implements predictive coding and topic modelling by automating reviews, resulting in reduced labor costs and time spent during the lawyers review. 920 | * Understand the end to end flow of the solution, doing research and development for classification models, predictive analysis and mining of the information present in text data. Worked on analyzing the outputs and precision monitoring for the entire tool. 921 | * TAR assists in predictive coding, topic modelling from the evidence by following EY standards. Developed the classifier models in order to identify ""red flags"" and fraud-related issues. 922 | 923 | Tools & Technologies: Python, scikit-learn, tfidf, word2vec, doc2vec, cosine similarity, Naïve Bayes, LDA, NMF for topic modelling, Vader and text blob for sentiment analysis. Matplot lib, Tableau dashboard for reporting. 924 | 925 | MULTIPLE DATA SCIENCE AND ANALYTIC PROJECTS (USA CLIENTS) 926 | TEXT ANALYTICS - MOTOR VEHICLE CUSTOMER REVIEW DATA * Received customer feedback survey data for past one year. Performed sentiment (Positive, Negative & Neutral) and time series analysis on customer comments across all 4 categories. 927 | * Created heat map of terms by survey category based on frequency of words * Extracted Positive and Negative words across all the Survey categories and plotted Word cloud. 928 | * Created customized tableau dashboards for effective reporting and visualizations. 929 | CHATBOT * Developed a user friendly chatbot for one of our Products which handle simple questions about hours of operation, reservation options and so on. 930 | * This chat bot serves entire product related questions. Giving overview of tool via QA platform and also give recommendation responses so that user question to build chain of relevant answer. 931 | * This too has intelligence to build the pipeline of questions as per user requirement and asks the relevant /recommended questions. 932 | 933 | Tools & Technologies: Python, Natural language processing, NLTK, spacy, topic modelling, Sentiment analysis, Word Embedding, scikit-learn, JavaScript/JQuery, SqlServer 934 | 935 | INFORMATION GOVERNANCE 936 | Organizations to make informed decisions about all of the information they store. The integrated Information Governance portfolio synthesizes intelligence across unstructured data sources and facilitates action to ensure organizations are best positioned to counter information risk. 937 | * Scan data from multiple sources of formats and parse different file formats, extract Meta data information, push results for indexing elastic search and created customized, interactive dashboards using kibana. 938 | * Preforming ROT Analysis on the data which give information of data which helps identify content that is either Redundant, Outdated, or Trivial. 939 | * Preforming full-text search analysis on elastic search with predefined methods which can tag as (PII) personally identifiable information (social security numbers, addresses, names, etc.) which frequently targeted during cyber-attacks. 940 | Tools & Technologies: Python, Flask, Elastic Search, Kibana 941 | 942 | FRAUD ANALYTIC PLATFORM 943 | Fraud Analytics and investigative platform to review all red flag cases. 944 | • FAP is a Fraud Analytics and investigative platform with inbuilt case manager and suite of Analytics for various ERP systems. 945 | * It can be used by clients to interrogate their Accounting systems for identifying the anomalies which can be indicators of fraud by running advanced analytics 946 | Tools & Technologies: HTML, JavaScript, SqlServer, JQuery, CSS, Bootstrap, Node.js, D3.js, DC.js" 947 | C0022,"Education Details 948 | May 2013 to May 2017 B.E UIT-RGPV 949 | Data Scientist 950 | 951 | Data Scientist - Matelabs 952 | Skill Details 953 | Python- Exprience - Less than 1 year months 954 | Statsmodels- Exprience - 12 months 955 | AWS- Exprience - Less than 1 year months 956 | Machine learning- Exprience - Less than 1 year months 957 | Sklearn- Exprience - Less than 1 year months 958 | Scipy- Exprience - Less than 1 year months 959 | Keras- Exprience - Less than 1 year monthsCompany Details 960 | company - Matelabs 961 | description - ML Platform for business professionals, dummies and enthusiasts. 962 | 60/A Koramangala 5th block, 963 | Achievements/Tasks behind sukh sagar, Bengaluru, 964 | India Developed and deployed auto preprocessing steps of machine learning mainly missing value 965 | treatment, outlier detection, encoding, scaling, feature selection and dimensionality reduction. 966 | Deployed automated classification and regression model. 967 | linkedin.com/in/aditya-rathore- 968 | b4600b146 Reasearch and deployed the time series forecasting model ARIMA, SARIMAX, Holt-winter and 969 | Prophet. 970 | Worked on meta-feature extracting problem. 971 | github.com/rathorology 972 | Implemented a state of the art research paper on outlier detection for mixed attributes. 973 | company - Matelabs 974 | description - " 975 | C0023,"Areas of Interest Deep Learning, Control System Design, Programming in-Python, Electric Machinery, Web Development, Analytics Technical Activities q Hindustan Aeronautics Limited, Bangalore - For 4 weeks under the guidance of Mr. Satish, Senior Engineer in the hangar of Mirage 2000 fighter aircraft Technical Skills Programming Matlab, Python and Java, LabView, Python WebFrameWork-Django, Flask, LTSPICE-intermediate Languages and and MIPOWER-intermediate, Github (GitBash), Jupyter Notebook, Xampp, MySQL-Basics, Python Software Packages Interpreters-Anaconda, Python2, Python3, Pycharm, Java IDE-Eclipse Operating Systems Windows, Ubuntu, Debian-Kali Linux Education Details 976 | January 2019 B.Tech. Electrical and Electronics Engineering Manipal Institute of Technology 977 | January 2015 DEEKSHA CENTER 978 | January 2013 Little Flower Public School 979 | August 2000 Manipal Academy of Higher 980 | DATA SCIENCE 981 | 982 | DATA SCIENCE AND ELECTRICAL ENTHUSIAST 983 | Skill Details 984 | Data Analysis- Exprience - Less than 1 year months 985 | excel- Exprience - Less than 1 year months 986 | Machine Learning- Exprience - Less than 1 year months 987 | mathematics- Exprience - Less than 1 year months 988 | Python- Exprience - Less than 1 year months 989 | Matlab- Exprience - Less than 1 year months 990 | Electrical Engineering- Exprience - Less than 1 year months 991 | Sql- Exprience - Less than 1 year monthsCompany Details 992 | company - THEMATHCOMPANY 993 | description - I am currently working with a Casino based operator(name not to be disclosed) in Macau.I need to segment the customers who visit their property based on the value the patrons bring into the company.Basically prove that the segmentation can be done in much better way than the current system which they have with proper numbers to back it up.Henceforth they can implement target marketing strategy to attract their customers who add value to the business." 994 | C0024,"Skills • R • Python • SAP HANA • Tableau • SAP HANA SQL • SAP HANA PAL • MS SQL • SAP Lumira • C# • Linear Programming • Data Modelling • Advance Analytics • SCM Analytics • Retail Analytics •Social Media Analytics • NLP Education Details 995 | January 2017 to January 2018 PGDM Business Analytics Great Lakes Institute of Management & Illinois Institute of Technology 996 | January 2013 Bachelor of Engineering Electronics and Communication Bengaluru, Karnataka New Horizon College of Engineering, Bangalore Visvesvaraya Technological University 997 | Data Science Consultant 998 | 999 | Consultant - Deloitte USI 1000 | Skill Details 1001 | LINEAR PROGRAMMING- Exprience - 6 months 1002 | RETAIL- Exprience - 6 months 1003 | RETAIL MARKETING- Exprience - 6 months 1004 | SCM- Exprience - 6 months 1005 | SQL- Exprience - Less than 1 year months 1006 | Deep Learning- Exprience - Less than 1 year months 1007 | Machine learning- Exprience - Less than 1 year months 1008 | Python- Exprience - Less than 1 year months 1009 | R- Exprience - Less than 1 year monthsCompany Details 1010 | company - Deloitte USI 1011 | description - The project involved analysing historic deals and coming with insights to optimize future deals. 1012 | Role: Was given raw data, carried out end to end analysis and presented insights to client. 1013 | Key Responsibilities: 1014 | • Extract data from client systems across geographies. 1015 | • Understand and build reports in tableau. Infer meaningful insights to optimize prices and find out process blockades. 1016 | Technical Environment: R, Tableau. 1017 | 1018 | Industry: Cross Industry 1019 | Service Area: Cross Industry - Products 1020 | Project Name: Handwriting recognition 1021 | Consultant: 3 months. 1022 | The project involved taking handwritten images and converting them to digital text images by object detection and sentence creation. 1023 | Role: I was developing sentence correction functionality. 1024 | Key Responsibilities: 1025 | • Gather data large enough to capture all English words 1026 | • Train LSTM models on words. 1027 | Technical Environment: Python. 1028 | 1029 | Industry: Finance 1030 | Service Area: Financial Services - BI development Project Name: SWIFT 1031 | Consultant: 8 months. 1032 | The project was to develop an analytics infrastructure on top of SAP S/4, it would user to view 1033 | financial reports to respective departments. Reporting also included forecasting expenses. 1034 | Role: I was leading the offshore team. 1035 | Key Responsibilities: 1036 | • Design & Develop data models for reporting. 1037 | • Develop ETL for data flow 1038 | • Validate various reports. 1039 | Technical Environment: SAP HANA, Tableau, SAP AO. 1040 | 1041 | Industry: Healthcare Analytics 1042 | Service Area: Life Sciences - Product development Project Name: Clinical Healthcare System 1043 | Consultant: 2 months. 1044 | The project was to develop an analytics infrastructure on top of Argus, it would allow users to query faster and provide advance analytics capabilities. 1045 | Role: I was involved from design to deploy phase, performed a lot of data restructuring and built 1046 | models for insights. 1047 | Key Responsibilities: 1048 | • Design & Develop data models for reporting. 1049 | • Develop and deploy analytical models. 1050 | • Validate various reports. 1051 | Technical Environment: Data Modelling, SAP HANA, Tableau, NLP. 1052 | 1053 | Industry: FMCG 1054 | Service Area: Trade & Promotion 1055 | Project Name: Consumption Based Planning for Flowers Foods Consultant; 8 months. 1056 | The project involved setting up of CRM and CBP modules. 1057 | Role: I was involved in key data decomposition activities and setting up the base for future year 1058 | forecast. Over the course of the project I developed various models and carried out key 1059 | performance improvements. 1060 | Key Responsibilities: 1061 | • Design & Develop HANA models for decomposition. 1062 | • Develop data flow for forecast. 1063 | • Developed various views for reporting of Customer/Sales/Funds. 1064 | • Validate various reports in BOBJ. 1065 | Technical Environment: Data Modelling, SAP HANA, BOBJ, Time Series Forecasting. 1066 | 1067 | Internal Initiative Industry: FMCG 1068 | Customer Segmentation and RFM analysis Consultant; 3 months. 1069 | The initiative involved setting up of HANA-Python interface and advance analytics on Python. Over the course I had successfully segmented data into five core segments using K-means and carried out RFM analysis in Python. Also developed algorithm to categorize any new customer under the defined buckets. 1070 | Technical Environment: Anaconda3, Python3.6, HANA SPS12 1071 | 1072 | Industry: Telecom Invoice state detection Consultant; 1 months. 1073 | The initiative was to reduce the manual effort in verifying closed and open invoices manually, it 1074 | involved development to a decision tree to classify open/closed invoices. This enabled effort 1075 | reduction by 60%. 1076 | Technical Environment: R, SAP PAL, SAP HANA SPS12 1077 | 1078 | Accenture Experience 1079 | Industry: Analytics - Cross Industry 1080 | In Process Analytics for SAP Senior Developer; 19 months. 1081 | Accenture Solutions Pvt. Ltd., India 1082 | The project involved development of SAP analytics tool - In Process Analytics (IPA) . My role was to develop database objects and data models to provide operational insights to clients. 1083 | Role: I have developed various Finance related KPIs and spearheaded various deployments. 1084 | Introduced SAP Predictive analytics to reduce development time and reuse functionalities for KPIs and prepared production planning reports. 1085 | Key Responsibilities: 1086 | • Involved in information gather phase. 1087 | • Designed and implemented SAP HANA data modelling using Attribute View, Analytic View, and 1088 | Calculation View. 1089 | • Developed various KPI's individually using complex SQL scripts in Calculation views. 1090 | • Created procedures in HANA Database. 1091 | • Took ownership and developed Dashboard functionality. 1092 | • Involved in building data processing algorithms to be executed in R server for cluster analysis. 1093 | Technical Environment: R, SAP HANA, T-SQL. 1094 | Industry: Cross Industry 1095 | Accenture Testing Accelerator for SAP Database Developer; 21 months. 1096 | Accenture Solutions Pvt. Ltd., India 1097 | Role: I have taken care of all development activities for the ATAS tool and have also completed 1098 | various deployments of the product. 1099 | Apart from these activities I was also actively involved in maintenance of the database servers 1100 | (Production & Quality) 1101 | Key Responsibilities: 1102 | • Analyzing business requirements, understanding the scope, getting requirements clarified 1103 | interacting with business and further transform all requirements to generate attribute 1104 | mapping documents and reviewing mapping specification documentation 1105 | • Create / Update database objects like tables, views, stored procedures, function, and packages 1106 | • Monitored SQL Server Error Logs and Application Logs through SQL Server Agent 1107 | • Prepared Data Flow Diagrams, Entity Relationship Diagrams using UML 1108 | • Responsible for Designing, developing and Normalization of database tables 1109 | • Experience in performance tuning using SQL profiler. 1110 | • Involved in QA, UAT, knowledge transfer and support activities 1111 | Technical Environment: SQL Server 2008/2014, Visual Studio 2010, Windows Server, Performance 1112 | Monitor, SQL Server Profiler, C#, PL-SQL, T-SQL." 1113 | C0025,"Education Details 1114 | MCA YMCAUST, Faridabad, Haryana 1115 | Data Science internship 1116 | 1117 | 1118 | Skill Details 1119 | Data Structure- Exprience - Less than 1 year months 1120 | C- Exprience - Less than 1 year months 1121 | Data Analysis- Exprience - Less than 1 year months 1122 | Python- Exprience - Less than 1 year months 1123 | Core Java- Exprience - Less than 1 year months 1124 | Database Management- Exprience - Less than 1 year monthsCompany Details 1125 | company - Itechpower 1126 | description - " 1127 | C0026,"SKILLS C Basics, IOT, Python, MATLAB, Data Science, Machine Learning, HTML, Microsoft Word, Microsoft Excel, Microsoft Powerpoint. RECOGNITION Academic Secured First place in B.Tech.Education Details 1128 | August 2014 to May 2018 B.Tech. Ghatkesar, Andhra Pradesh Aurora's Scientific and Technological Institute 1129 | June 2012 to May 2014 Secondary Education Warangal, Telangana SR Junior College 1130 | Data Science 1131 | 1132 | 1133 | Skill Details 1134 | MS OFFICE- Exprience - Less than 1 year months 1135 | C- Exprience - Less than 1 year months 1136 | machine learning- Exprience - Less than 1 year months 1137 | data science- Exprience - Less than 1 year months 1138 | Matlab- Exprience - Less than 1 year monthsCompany Details 1139 | company - 1140 | description - " 1141 | C0027,"Skills • Python • Tableau • Data Visualization • R Studio • Machine Learning • Statistics IABAC Certified Data Scientist with versatile experience over 1+ years in managing business, data science consulting and leading innovation projects, bringing business ideas to working real world solutions. Being a strong advocator of augmented era, where human capabilities are enhanced by machines, Fahed is passionate about bringing business concepts in area of machine learning, AI, robotics etc., to real life solutions.Education Details 1142 | January 2017 B. Tech Computer Science & Engineering Mohali, Punjab Indo Global College of Engineering 1143 | Data Science Consultant 1144 | 1145 | Data Science Consultant - Datamites 1146 | Skill Details 1147 | MACHINE LEARNING- Exprience - 13 months 1148 | PYTHON- Exprience - 24 months 1149 | SOLUTIONS- Exprience - 24 months 1150 | DATA SCIENCE- Exprience - 24 months 1151 | DATA VISUALIZATION- Exprience - 24 months 1152 | Tableau- Exprience - 24 monthsCompany Details 1153 | company - Datamites 1154 | description - • Analyzed and processed complex data sets using advanced querying, visualization and analytics tools. 1155 | • Responsible for loading, extracting and validation of client data. 1156 | • Worked on manipulating, cleaning & processing data using python. 1157 | • Used Tableau for data visualization. 1158 | company - Heretic Solutions Pvt Ltd 1159 | description - • Worked closely with business to identify issues and used data to propose solutions for effective decision making. 1160 | • Manipulating, cleansing & processing data using Python, Excel and R. 1161 | • Analyzed raw data, drawing conclusions & developing recommendations. 1162 | • Used machine learning tools and statistical techniques to produce solutions to problems." 1163 | C0028,"Education Details 1164 | B.Tech Rayat and Bahra Institute of Engineering and Biotechnology 1165 | Data Science 1166 | 1167 | Data Science 1168 | Skill Details 1169 | Numpy- Exprience - Less than 1 year months 1170 | Machine Learning- Exprience - Less than 1 year months 1171 | Tensorflow- Exprience - Less than 1 year months 1172 | Scikit- Exprience - Less than 1 year months 1173 | Python- Exprience - Less than 1 year months 1174 | GCP- Exprience - Less than 1 year months 1175 | Pandas- Exprience - Less than 1 year months 1176 | Neural Network- Exprience - Less than 1 year monthsCompany Details 1177 | company - Wipro 1178 | description - Bhawana Aggarwal 1179 | E-Mail:bhawana.chd@gmail.com 1180 | Phone: 09876971076 1181 | VVersatile, high-energy professional targeting challenging assignments in Machine 1182 | PROFILE SUMMARY 1183 | ▪ An IT professional with knowledge and experience of 2 years in Wipro Technologies in Machine 1184 | Learning, Deep Learning, Data Science, Python, Software Development. 1185 | ▪ Skilled in managing end-to-end development and software products / projects from inception, requirement 1186 | specs, planning, designing, implementation, configuration and documentation. 1187 | ▪ Knowledge on Python , Machine Learning, Deep Learning, data Science, Algorithms, Neural Network, 1188 | NLP, GCP. 1189 | ▪ Knowledge on Python Libraries like Numpy, Pandas, Seaborn , Matplotlib, Cufflinks. 1190 | ▪ Knowledge on different algorithms in Machine learning like KNN, Decision Tree, Bias variance Trade off, 1191 | Support vector Machine(SVM),Logistic Regression, Neural networks. 1192 | ▪ Have knowledge on unsupervised, Supervised and reinforcement data. 1193 | ▪ Programming experience in relational platforms like MySQL,Oracle. 1194 | ▪ Have knowledge on Some programming language like C++,Java. 1195 | ▪ Experience in cloud based environment like Google Cloud. 1196 | ▪ Working on different Operating System like Linux, Ubuntu, Windows. 1197 | ▪ Good interpersonal and communication skills. 1198 | ▪ Problem solving skills with the ability to think laterally, and to think with a medium term and long term 1199 | perspective 1200 | ▪ Flexibility and an open attitude to change. 1201 | ▪ Ability to create, define and own frameworks with a strong emphasis on code reusability. 1202 | TECHNICAL SKILLS 1203 | Programming Languages Python, C 1204 | Libraries Seaborn, Numpy, Pandas, Cufflinks, Matplotlib 1205 | Algorithms 1206 | KNN, Decision Tree, Linear regression, Logistic Regression, Neural Networks, K means clustering, 1207 | Tensorflow, SVM 1208 | Databases SQL, Oracle 1209 | Operating Systems Linux, Window 1210 | Development Environments NetBeans, Notebooks, Sublime 1211 | Ticketing tools Service Now, Remedy 1212 | Education 1213 | UG Education: 1214 | B.Tech (Computer Science) from Rayat and Bahra Institute of Engineering and Biotechnology passed with 78.4%in 1215 | 2016. 1216 | Schooling: 1217 | XII in 2012 from Moti Ram Arya Sr. Secondary School(Passed with 78.4%) 1218 | X in 2010 from Valley Public School (Passed with 9.4 CGPA) 1219 | WORK EXPERINCE 1220 | Title : Wipro Neural Intelligence Platform 1221 | Team Size : 5 1222 | Brief: Wipro’s Neural Intelligence Platform harnesses the power of automation and artificial intelligence 1223 | technologies—natural language processing (NLP), cognitive, machine learning, and analytics. The platform 1224 | comprises three layers: a data engagement platform that can easily access and manage multiple structured and 1225 | unstructured data sources; an “intent assessment and reasoning” engine that includes sentiment and predictive 1226 | analytics; and a deep machine learning engine that can sense, act, and learn over time. The project entailed 1227 | automating responses to user queries at the earliest. The Monster Bot using the power of Deep Machine Learning, 1228 | NLP to handle such queries. User can see the how their queries can be answered quickly like allL1 activities can be 1229 | eliminated. 1230 | Entity Extractor -> This involves text extraction and NLP for fetching out important information from the text like 1231 | dates, names, places, contact numbers etc. This involves Regex, Bluemix NLU api’s and machine learning using 1232 | Tensor flow for further learning of new entities. 1233 | Classifier ->This involves the classifications of classes, training of dataset and predicting the output using the SKLearn 1234 | classifier (MNB, SVM, SGD as Classifier) and SGD for the optimization to map the user queries with the best 1235 | suited response and make the system efficient. 1236 | NER: A Deep Learning NER Model is trained to extract the entities from the text. Entities like Roles, Skills, 1237 | Organizations can be extracted from raw text. RNN(LSTM) Bidirectional model is trained for extracting such entities 1238 | using Keras TensorFlow framework. 1239 | OTHER PROJECTS 1240 | Title : Diabetes Detection 1241 | Brief : Developed the software which can detect whether the person is suffering from Diabetes or not and got the third 1242 | prize in it. 1243 | TRAINING AND CERTIFICATIONS 1244 | Title: Python Training, Machine Learning, Data Science, Deep Learning 1245 | Organization: Udemy, Coursera (Machine Learning, Deep Learning) 1246 | Personal Profile 1247 | Father’s Name :Mr. Tirlok Aggarwal 1248 | Language Known : English & Hindi 1249 | Marital Status :Single 1250 | Date of Birth(Gender):1993-12-20(YYYY-MM-DD) (F) 1251 | company - Wipro 1252 | description - Developing programs in Python. 1253 | company - Wipro 1254 | description - Title : Wipro Neural Intelligence Platform 1255 | Team Size : 5 1256 | Brief: Wipro’s Neural Intelligence Platform harnesses the power of automation and artificial intelligence 1257 | technologies—natural language processing (NLP), cognitive, machine learning, and analytics. The platform 1258 | comprises three layers: a data engagement platform that can easily access and manage multiple structured and 1259 | unstructured data sources; an “intent assessment and reasoning” engine that includes sentiment and predictive 1260 | analytics; and a deep machine learning engine that can sense, act, and learn over time. The project entailed 1261 | automating responses to user queries at the earliest. The Monster Bot using the power of Deep Machine Learning, 1262 | NLP to handle such queries. User can see the how their queries can be answered quickly like allL1 activities can be 1263 | eliminated. 1264 | Entity Extractor -> This involves text extraction and NLP for fetching out important information from the text like 1265 | dates, names, places, contact numbers etc. This involves Regex, Bluemix NLU api’s and machine learning using 1266 | Tensor flow for further learning of new entities. 1267 | Classifier ->This involves the classifications of classes, training of dataset and predicting the output using the SKLearn 1268 | classifier (MNB, SVM, SGD as Classifier) and SGD for the optimization to map the user queries with the best 1269 | suited response and make the system efficient. 1270 | NER: A Deep Learning NER Model is trained to extract the entities from the text. Entities like Roles, Skills, 1271 | Organizations can be extracted from raw text. RNN(LSTM) Bidirectional model is trained for extracting such entities 1272 | using Keras TensorFlow framework. 1273 | company - Wipro Technologies 1274 | description - An IT professional with knowledge and experience of 2 years in Wipro Technologies in Machine 1275 | Learning, Deep Learning, Data Science, Python, Software Development. 1276 | ▪ Skilled in managing end-to-end development and software products / projects from inception, requirement 1277 | specs, planning, designing, implementation, configuration and documentation. 1278 | ▪ Knowledge on Python , Machine Learning, Deep Learning, data Science, Algorithms, Neural Network, 1279 | NLP, GCP. 1280 | ▪ Knowledge on Python Libraries like Numpy, Pandas, Seaborn , Matplotlib, Cufflinks. 1281 | ▪ Knowledge on different algorithms in Machine learning like KNN, Decision Tree, Bias variance Trade off, 1282 | Support vector Machine(SVM),Logistic Regression, Neural networks. 1283 | ▪ Have knowledge on unsupervised, Supervised and reinforcement data. 1284 | ▪ Programming experience in relational platforms like MySQL,Oracle. 1285 | ▪ Have knowledge on Some programming language like C++,Java. 1286 | ▪ Experience in cloud based environment like Google Cloud. 1287 | ▪ Working on different Operating System like Linux, Ubuntu, Windows. 1288 | ▪ Good interpersonal and communication skills. 1289 | ▪ Problem solving skills with the ability to think laterally, and to think with a medium term and long term 1290 | perspective 1291 | ▪ Flexibility and an open attitude to change. 1292 | ▪ Ability to create, define and own frameworks with a strong emphasis on code reusability." 1293 | C0029,"Personal Skills ➢ Ability to quickly grasp technical aspects and willingness to learn ➢ High energy levels & Result oriented. Education Details 1294 | January 2018 Master of Engineering Computer Technology & Application Bhopal, Madhya Pradesh Truba Institute of Engineering & Information Technology 1295 | January 2010 B.E. computer science Bhopal, Madhya Pradesh RKDF Institute of Science and Technology College of Engineering 1296 | January 2006 Polytechnic Information Technology Vidisha, Madhya Pradesh SATI Engineering College in Vidisha 1297 | January 2003 M.tech Thesis Detail BMCH School in Ganj basoda 1298 | Data science 1299 | 1300 | I have six month experience in Data Science. Key Skills: - Experience in Machine Learning, Deep Leaning, NLP, Python, SQL, Web Scraping Good knowledge in computer subjects and ability to update 1301 | Skill Details 1302 | Experience in Machine Learning, Deep Learning, NLP, Python, SQL, Web Crawling, HTML,CSS.- Exprience - Less than 1 year monthsCompany Details 1303 | company - RNT.AI Technology Solution 1304 | description - Text classification using Machine learning Algorithms with python. 1305 | Practical knowledge of Deep learning algorithms such as  Recurrent Neural Networks(RNN). 1306 | Develop custom data models and algorithms to apply to dataset 1307 | Experience with Python packages like Pandas, Scikit-learn, Tensor Flow, Numpy, Matplotliv, NLTK. 1308 | Comfort with SQL,  MYSQL 1309 | Sentiment analysis. 1310 |  Apply leave Dataset using classification technique like Tf--idf , LSA with cosine similarity using Machine learning Algorithms. 1311 | Web crawling using Selenium web driver and Beautiful Soup with python. 1312 | company - Life Insurance Corporation of India Bhopal 1313 | description - ü Explaining policy features and the benefits 1314 | ü Updated knowledge of life insurance products and shared with customers" 1315 | C0030,"Expertise − Data and Quantitative Analysis − Decision Analytics − Predictive Modeling − Data-Driven Personalization − KPI Dashboards − Big Data Queries and Interpretation − Data Mining and Visualization Tools − Machine Learning Algorithms − Business Intelligence (BI) − Research, Reports and Forecasts Education Details 1316 | PGP in Data Science Mumbai, Maharashtra Aegis School of data science & Business 1317 | B.E. in Electronics & Communication Electronics & Communication Indore, Madhya Pradesh IES IPS Academy 1318 | Data Scientist 1319 | 1320 | Data Scientist with PR Canada 1321 | Skill Details 1322 | Algorithms- Exprience - 6 months 1323 | BI- Exprience - 6 months 1324 | Business Intelligence- Exprience - 6 months 1325 | Machine Learning- Exprience - 24 months 1326 | Visualization- Exprience - 24 months 1327 | spark- Exprience - 24 months 1328 | python- Exprience - 36 months 1329 | tableau- Exprience - 36 months 1330 | Data Analysis- Exprience - 24 monthsCompany Details 1331 | company - Aegis school of Data Science & Business 1332 | description - Mostly working on industry project for providing solution along with Teaching Appointments: Teach undergraduate and graduate-level courses in Spark and Machine Learning as an adjunct faculty member at Aegis School of Data Science, Mumbai (2017 to Present) 1333 | company - Aegis school of Data & Business 1334 | description - Data Science Intern, Nov 2015 to Jan 2016 1335 | 1336 | Furnish executive leadership team with insights, analytics, reports and recommendations enabling effective strategic planning across all business units, distribution channels and product lines. 1337 | 1338 | ➔ Chat Bot using AWS LEX and Tensor flow Python 1339 | The goal of project creates a chat bot for an academic institution or university to handle queries related courses offered by that institute. The objective of this task is to reduce human efforts as well as reduce man made errors. Even by this companies handle their client 24x7. In this case companies are academic institutions and clients are participants or students. 1340 | ➔ Web scraping using Selenium web driver Python 1341 | The task is to scrap the data from the online messaging portal in a text format and have to find the pattern form it. 1342 | ➔ Data Visualization and Data insights Hadoop Eco System, Hive, PySpark, QlikSense 1343 | The goal of this project is to build a Business Solutions to a Internet Service Provider Company, like handling data which is generated per day basis, for that we have to visualize that data and find the usage pattern form it and have a generate a reports. 1344 | ➔ Image Based Fraud Detection Microsoft Face API, PySpark, Open CV 1345 | The main goal of project is Recognize similarity for a face to given Database images. Face recognition is the recognizing a special face from set of different faces. Face is extracted and then compared with the database Image if that Image recognized then the person already applied for loan from somewhere else and now hiding his or her identity, this is how we are going to prevent the frauds in the initial stage itself. 1346 | ➔ Churn Analysis for Internet Service Provider R, Python, Machine Learning, Hadoop 1347 | The objective is to identify the customer who is likely to churn in a given period of time; we have to pretend the customer giving incentive offers. 1348 | ➔ Sentiment Analysis Python, NLP, Apache Spark service in IBM Bluemix. 1349 | This project is highly emphasis on tweets from Twitter data were taken for mobile networks service provider to do a sentiment analysis and analyze whether the expressed opinion was positive, negative or neutral, capture the emotions of the tweets and comparative analysis. 1350 | 1351 | Quantifiable Results: 1352 | − Mentored 7-12 Data Science Enthusiast each year that have all since gone on to graduate school in Data Science and Business Analytics. 1353 | − Reviewed and evaluated 20-40 Research Papers on Data Science for one of the largest Data Science Conference called Data Science Congress by Aegis School of Business Mumbai. 1354 | − Heading a solution providing organization called Data Science Delivered into Aegis school of Data Science Mumbai and managed 4-5 live projects using Data Science techniques. 1355 | − Working for some social cause with the help of Data Science for Social Goods Committee, where our team developed a product called ""Let's find a missing Child"" for helping society. 1356 | company - IBM India pvt ltd 1357 | description - Mostly worked on blumix and IBM Watson for Data science." 1358 | C0031,"Skills * Programming Languages: Python (pandas, numpy, scipy, scikit-learn, matplotlib), Sql, Java, JavaScript/JQuery. * Machine learning: Regression, SVM, Naïve Bayes, KNN, Random Forest, Decision Trees, Boosting techniques, Cluster Analysis, Word Embedding, Sentiment Analysis, Natural Language processing, Dimensionality reduction, Topic Modelling (LDA, NMF), PCA & Neural Nets. * Database Visualizations: Mysql, SqlServer, Cassandra, Hbase, ElasticSearch D3.js, DC.js, Plotly, kibana, matplotlib, ggplot, Tableau. * Others: Regular Expression, HTML, CSS, Angular 6, Logstash, Kafka, Python Flask, Git, Docker, computer vision - Open CV and understanding of Deep learning.Education Details 1359 | 1360 | Data Science Assurance Associate 1361 | 1362 | Data Science Assurance Associate - Ernst & Young LLP 1363 | Skill Details 1364 | JAVASCRIPT- Exprience - 24 months 1365 | jQuery- Exprience - 24 months 1366 | Python- Exprience - 24 monthsCompany Details 1367 | company - Ernst & Young LLP 1368 | description - Fraud Investigations and Dispute Services Assurance 1369 | TECHNOLOGY ASSISTED REVIEW 1370 | TAR (Technology Assisted Review) assists in accelerating the review process and run analytics and generate reports. 1371 | * Core member of a team helped in developing automated review platform tool from scratch for assisting E discovery domain, this tool implements predictive coding and topic modelling by automating reviews, resulting in reduced labor costs and time spent during the lawyers review. 1372 | * Understand the end to end flow of the solution, doing research and development for classification models, predictive analysis and mining of the information present in text data. Worked on analyzing the outputs and precision monitoring for the entire tool. 1373 | * TAR assists in predictive coding, topic modelling from the evidence by following EY standards. Developed the classifier models in order to identify ""red flags"" and fraud-related issues. 1374 | 1375 | Tools & Technologies: Python, scikit-learn, tfidf, word2vec, doc2vec, cosine similarity, Naïve Bayes, LDA, NMF for topic modelling, Vader and text blob for sentiment analysis. Matplot lib, Tableau dashboard for reporting. 1376 | 1377 | MULTIPLE DATA SCIENCE AND ANALYTIC PROJECTS (USA CLIENTS) 1378 | TEXT ANALYTICS - MOTOR VEHICLE CUSTOMER REVIEW DATA * Received customer feedback survey data for past one year. Performed sentiment (Positive, Negative & Neutral) and time series analysis on customer comments across all 4 categories. 1379 | * Created heat map of terms by survey category based on frequency of words * Extracted Positive and Negative words across all the Survey categories and plotted Word cloud. 1380 | * Created customized tableau dashboards for effective reporting and visualizations. 1381 | CHATBOT * Developed a user friendly chatbot for one of our Products which handle simple questions about hours of operation, reservation options and so on. 1382 | * This chat bot serves entire product related questions. Giving overview of tool via QA platform and also give recommendation responses so that user question to build chain of relevant answer. 1383 | * This too has intelligence to build the pipeline of questions as per user requirement and asks the relevant /recommended questions. 1384 | 1385 | Tools & Technologies: Python, Natural language processing, NLTK, spacy, topic modelling, Sentiment analysis, Word Embedding, scikit-learn, JavaScript/JQuery, SqlServer 1386 | 1387 | INFORMATION GOVERNANCE 1388 | Organizations to make informed decisions about all of the information they store. The integrated Information Governance portfolio synthesizes intelligence across unstructured data sources and facilitates action to ensure organizations are best positioned to counter information risk. 1389 | * Scan data from multiple sources of formats and parse different file formats, extract Meta data information, push results for indexing elastic search and created customized, interactive dashboards using kibana. 1390 | * Preforming ROT Analysis on the data which give information of data which helps identify content that is either Redundant, Outdated, or Trivial. 1391 | * Preforming full-text search analysis on elastic search with predefined methods which can tag as (PII) personally identifiable information (social security numbers, addresses, names, etc.) which frequently targeted during cyber-attacks. 1392 | Tools & Technologies: Python, Flask, Elastic Search, Kibana 1393 | 1394 | FRAUD ANALYTIC PLATFORM 1395 | Fraud Analytics and investigative platform to review all red flag cases. 1396 | • FAP is a Fraud Analytics and investigative platform with inbuilt case manager and suite of Analytics for various ERP systems. 1397 | * It can be used by clients to interrogate their Accounting systems for identifying the anomalies which can be indicators of fraud by running advanced analytics 1398 | Tools & Technologies: HTML, JavaScript, SqlServer, JQuery, CSS, Bootstrap, Node.js, D3.js, DC.js" 1399 | C0032,"Education Details 1400 | May 2013 to May 2017 B.E UIT-RGPV 1401 | Data Scientist 1402 | 1403 | Data Scientist - Matelabs 1404 | Skill Details 1405 | Python- Exprience - Less than 1 year months 1406 | Statsmodels- Exprience - 12 months 1407 | AWS- Exprience - Less than 1 year months 1408 | Machine learning- Exprience - Less than 1 year months 1409 | Sklearn- Exprience - Less than 1 year months 1410 | Scipy- Exprience - Less than 1 year months 1411 | Keras- Exprience - Less than 1 year monthsCompany Details 1412 | company - Matelabs 1413 | description - ML Platform for business professionals, dummies and enthusiasts. 1414 | 60/A Koramangala 5th block, 1415 | Achievements/Tasks behind sukh sagar, Bengaluru, 1416 | India Developed and deployed auto preprocessing steps of machine learning mainly missing value 1417 | treatment, outlier detection, encoding, scaling, feature selection and dimensionality reduction. 1418 | Deployed automated classification and regression model. 1419 | linkedin.com/in/aditya-rathore- 1420 | b4600b146 Reasearch and deployed the time series forecasting model ARIMA, SARIMAX, Holt-winter and 1421 | Prophet. 1422 | Worked on meta-feature extracting problem. 1423 | github.com/rathorology 1424 | Implemented a state of the art research paper on outlier detection for mixed attributes. 1425 | company - Matelabs 1426 | description - " 1427 | C0033,"Areas of Interest Deep Learning, Control System Design, Programming in-Python, Electric Machinery, Web Development, Analytics Technical Activities q Hindustan Aeronautics Limited, Bangalore - For 4 weeks under the guidance of Mr. Satish, Senior Engineer in the hangar of Mirage 2000 fighter aircraft Technical Skills Programming Matlab, Python and Java, LabView, Python WebFrameWork-Django, Flask, LTSPICE-intermediate Languages and and MIPOWER-intermediate, Github (GitBash), Jupyter Notebook, Xampp, MySQL-Basics, Python Software Packages Interpreters-Anaconda, Python2, Python3, Pycharm, Java IDE-Eclipse Operating Systems Windows, Ubuntu, Debian-Kali Linux Education Details 1428 | January 2019 B.Tech. Electrical and Electronics Engineering Manipal Institute of Technology 1429 | January 2015 DEEKSHA CENTER 1430 | January 2013 Little Flower Public School 1431 | August 2000 Manipal Academy of Higher 1432 | DATA SCIENCE 1433 | 1434 | DATA SCIENCE AND ELECTRICAL ENTHUSIAST 1435 | Skill Details 1436 | Data Analysis- Exprience - Less than 1 year months 1437 | excel- Exprience - Less than 1 year months 1438 | Machine Learning- Exprience - Less than 1 year months 1439 | mathematics- Exprience - Less than 1 year months 1440 | Python- Exprience - Less than 1 year months 1441 | Matlab- Exprience - Less than 1 year months 1442 | Electrical Engineering- Exprience - Less than 1 year months 1443 | Sql- Exprience - Less than 1 year monthsCompany Details 1444 | company - THEMATHCOMPANY 1445 | description - I am currently working with a Casino based operator(name not to be disclosed) in Macau.I need to segment the customers who visit their property based on the value the patrons bring into the company.Basically prove that the segmentation can be done in much better way than the current system which they have with proper numbers to back it up.Henceforth they can implement target marketing strategy to attract their customers who add value to the business." 1446 | C0034,"Skills • R • Python • SAP HANA • Tableau • SAP HANA SQL • SAP HANA PAL • MS SQL • SAP Lumira • C# • Linear Programming • Data Modelling • Advance Analytics • SCM Analytics • Retail Analytics •Social Media Analytics • NLP Education Details 1447 | January 2017 to January 2018 PGDM Business Analytics Great Lakes Institute of Management & Illinois Institute of Technology 1448 | January 2013 Bachelor of Engineering Electronics and Communication Bengaluru, Karnataka New Horizon College of Engineering, Bangalore Visvesvaraya Technological University 1449 | Data Science Consultant 1450 | 1451 | Consultant - Deloitte USI 1452 | Skill Details 1453 | LINEAR PROGRAMMING- Exprience - 6 months 1454 | RETAIL- Exprience - 6 months 1455 | RETAIL MARKETING- Exprience - 6 months 1456 | SCM- Exprience - 6 months 1457 | SQL- Exprience - Less than 1 year months 1458 | Deep Learning- Exprience - Less than 1 year months 1459 | Machine learning- Exprience - Less than 1 year months 1460 | Python- Exprience - Less than 1 year months 1461 | R- Exprience - Less than 1 year monthsCompany Details 1462 | company - Deloitte USI 1463 | description - The project involved analysing historic deals and coming with insights to optimize future deals. 1464 | Role: Was given raw data, carried out end to end analysis and presented insights to client. 1465 | Key Responsibilities: 1466 | • Extract data from client systems across geographies. 1467 | • Understand and build reports in tableau. Infer meaningful insights to optimize prices and find out process blockades. 1468 | Technical Environment: R, Tableau. 1469 | 1470 | Industry: Cross Industry 1471 | Service Area: Cross Industry - Products 1472 | Project Name: Handwriting recognition 1473 | Consultant: 3 months. 1474 | The project involved taking handwritten images and converting them to digital text images by object detection and sentence creation. 1475 | Role: I was developing sentence correction functionality. 1476 | Key Responsibilities: 1477 | • Gather data large enough to capture all English words 1478 | • Train LSTM models on words. 1479 | Technical Environment: Python. 1480 | 1481 | Industry: Finance 1482 | Service Area: Financial Services - BI development Project Name: SWIFT 1483 | Consultant: 8 months. 1484 | The project was to develop an analytics infrastructure on top of SAP S/4, it would user to view 1485 | financial reports to respective departments. Reporting also included forecasting expenses. 1486 | Role: I was leading the offshore team. 1487 | Key Responsibilities: 1488 | • Design & Develop data models for reporting. 1489 | • Develop ETL for data flow 1490 | • Validate various reports. 1491 | Technical Environment: SAP HANA, Tableau, SAP AO. 1492 | 1493 | Industry: Healthcare Analytics 1494 | Service Area: Life Sciences - Product development Project Name: Clinical Healthcare System 1495 | Consultant: 2 months. 1496 | The project was to develop an analytics infrastructure on top of Argus, it would allow users to query faster and provide advance analytics capabilities. 1497 | Role: I was involved from design to deploy phase, performed a lot of data restructuring and built 1498 | models for insights. 1499 | Key Responsibilities: 1500 | • Design & Develop data models for reporting. 1501 | • Develop and deploy analytical models. 1502 | • Validate various reports. 1503 | Technical Environment: Data Modelling, SAP HANA, Tableau, NLP. 1504 | 1505 | Industry: FMCG 1506 | Service Area: Trade & Promotion 1507 | Project Name: Consumption Based Planning for Flowers Foods Consultant; 8 months. 1508 | The project involved setting up of CRM and CBP modules. 1509 | Role: I was involved in key data decomposition activities and setting up the base for future year 1510 | forecast. Over the course of the project I developed various models and carried out key 1511 | performance improvements. 1512 | Key Responsibilities: 1513 | • Design & Develop HANA models for decomposition. 1514 | • Develop data flow for forecast. 1515 | • Developed various views for reporting of Customer/Sales/Funds. 1516 | • Validate various reports in BOBJ. 1517 | Technical Environment: Data Modelling, SAP HANA, BOBJ, Time Series Forecasting. 1518 | 1519 | Internal Initiative Industry: FMCG 1520 | Customer Segmentation and RFM analysis Consultant; 3 months. 1521 | The initiative involved setting up of HANA-Python interface and advance analytics on Python. Over the course I had successfully segmented data into five core segments using K-means and carried out RFM analysis in Python. Also developed algorithm to categorize any new customer under the defined buckets. 1522 | Technical Environment: Anaconda3, Python3.6, HANA SPS12 1523 | 1524 | Industry: Telecom Invoice state detection Consultant; 1 months. 1525 | The initiative was to reduce the manual effort in verifying closed and open invoices manually, it 1526 | involved development to a decision tree to classify open/closed invoices. This enabled effort 1527 | reduction by 60%. 1528 | Technical Environment: R, SAP PAL, SAP HANA SPS12 1529 | 1530 | Accenture Experience 1531 | Industry: Analytics - Cross Industry 1532 | In Process Analytics for SAP Senior Developer; 19 months. 1533 | Accenture Solutions Pvt. Ltd., India 1534 | The project involved development of SAP analytics tool - In Process Analytics (IPA) . My role was to develop database objects and data models to provide operational insights to clients. 1535 | Role: I have developed various Finance related KPIs and spearheaded various deployments. 1536 | Introduced SAP Predictive analytics to reduce development time and reuse functionalities for KPIs and prepared production planning reports. 1537 | Key Responsibilities: 1538 | • Involved in information gather phase. 1539 | • Designed and implemented SAP HANA data modelling using Attribute View, Analytic View, and 1540 | Calculation View. 1541 | • Developed various KPI's individually using complex SQL scripts in Calculation views. 1542 | • Created procedures in HANA Database. 1543 | • Took ownership and developed Dashboard functionality. 1544 | • Involved in building data processing algorithms to be executed in R server for cluster analysis. 1545 | Technical Environment: R, SAP HANA, T-SQL. 1546 | Industry: Cross Industry 1547 | Accenture Testing Accelerator for SAP Database Developer; 21 months. 1548 | Accenture Solutions Pvt. Ltd., India 1549 | Role: I have taken care of all development activities for the ATAS tool and have also completed 1550 | various deployments of the product. 1551 | Apart from these activities I was also actively involved in maintenance of the database servers 1552 | (Production & Quality) 1553 | Key Responsibilities: 1554 | • Analyzing business requirements, understanding the scope, getting requirements clarified 1555 | interacting with business and further transform all requirements to generate attribute 1556 | mapping documents and reviewing mapping specification documentation 1557 | • Create / Update database objects like tables, views, stored procedures, function, and packages 1558 | • Monitored SQL Server Error Logs and Application Logs through SQL Server Agent 1559 | • Prepared Data Flow Diagrams, Entity Relationship Diagrams using UML 1560 | • Responsible for Designing, developing and Normalization of database tables 1561 | • Experience in performance tuning using SQL profiler. 1562 | • Involved in QA, UAT, knowledge transfer and support activities 1563 | Technical Environment: SQL Server 2008/2014, Visual Studio 2010, Windows Server, Performance 1564 | Monitor, SQL Server Profiler, C#, PL-SQL, T-SQL." 1565 | C0035,"Education Details 1566 | MCA YMCAUST, Faridabad, Haryana 1567 | Data Science internship 1568 | 1569 | 1570 | Skill Details 1571 | Data Structure- Exprience - Less than 1 year months 1572 | C- Exprience - Less than 1 year months 1573 | Data Analysis- Exprience - Less than 1 year months 1574 | Python- Exprience - Less than 1 year months 1575 | Core Java- Exprience - Less than 1 year months 1576 | Database Management- Exprience - Less than 1 year monthsCompany Details 1577 | company - Itechpower 1578 | description - " 1579 | C0036,"SKILLS C Basics, IOT, Python, MATLAB, Data Science, Machine Learning, HTML, Microsoft Word, Microsoft Excel, Microsoft Powerpoint. RECOGNITION Academic Secured First place in B.Tech.Education Details 1580 | August 2014 to May 2018 B.Tech. Ghatkesar, Andhra Pradesh Aurora's Scientific and Technological Institute 1581 | June 2012 to May 2014 Secondary Education Warangal, Telangana SR Junior College 1582 | Data Science 1583 | 1584 | 1585 | Skill Details 1586 | MS OFFICE- Exprience - Less than 1 year months 1587 | C- Exprience - Less than 1 year months 1588 | machine learning- Exprience - Less than 1 year months 1589 | data science- Exprience - Less than 1 year months 1590 | Matlab- Exprience - Less than 1 year monthsCompany Details 1591 | company - 1592 | description - " 1593 | C0037,"Skills • Python • Tableau • Data Visualization • R Studio • Machine Learning • Statistics IABAC Certified Data Scientist with versatile experience over 1+ years in managing business, data science consulting and leading innovation projects, bringing business ideas to working real world solutions. Being a strong advocator of augmented era, where human capabilities are enhanced by machines, Fahed is passionate about bringing business concepts in area of machine learning, AI, robotics etc., to real life solutions.Education Details 1594 | January 2017 B. Tech Computer Science & Engineering Mohali, Punjab Indo Global College of Engineering 1595 | Data Science Consultant 1596 | 1597 | Data Science Consultant - Datamites 1598 | Skill Details 1599 | MACHINE LEARNING- Exprience - 13 months 1600 | PYTHON- Exprience - 24 months 1601 | SOLUTIONS- Exprience - 24 months 1602 | DATA SCIENCE- Exprience - 24 months 1603 | DATA VISUALIZATION- Exprience - 24 months 1604 | Tableau- Exprience - 24 monthsCompany Details 1605 | company - Datamites 1606 | description - • Analyzed and processed complex data sets using advanced querying, visualization and analytics tools. 1607 | • Responsible for loading, extracting and validation of client data. 1608 | • Worked on manipulating, cleaning & processing data using python. 1609 | • Used Tableau for data visualization. 1610 | company - Heretic Solutions Pvt Ltd 1611 | description - • Worked closely with business to identify issues and used data to propose solutions for effective decision making. 1612 | • Manipulating, cleansing & processing data using Python, Excel and R. 1613 | • Analyzed raw data, drawing conclusions & developing recommendations. 1614 | • Used machine learning tools and statistical techniques to produce solutions to problems." 1615 | C0038,"Education Details 1616 | B.Tech Rayat and Bahra Institute of Engineering and Biotechnology 1617 | Data Science 1618 | 1619 | Data Science 1620 | Skill Details 1621 | Numpy- Exprience - Less than 1 year months 1622 | Machine Learning- Exprience - Less than 1 year months 1623 | Tensorflow- Exprience - Less than 1 year months 1624 | Scikit- Exprience - Less than 1 year months 1625 | Python- Exprience - Less than 1 year months 1626 | GCP- Exprience - Less than 1 year months 1627 | Pandas- Exprience - Less than 1 year months 1628 | Neural Network- Exprience - Less than 1 year monthsCompany Details 1629 | company - Wipro 1630 | description - Bhawana Aggarwal 1631 | E-Mail:bhawana.chd@gmail.com 1632 | Phone: 09876971076 1633 | VVersatile, high-energy professional targeting challenging assignments in Machine 1634 | PROFILE SUMMARY 1635 | ▪ An IT professional with knowledge and experience of 2 years in Wipro Technologies in Machine 1636 | Learning, Deep Learning, Data Science, Python, Software Development. 1637 | ▪ Skilled in managing end-to-end development and software products / projects from inception, requirement 1638 | specs, planning, designing, implementation, configuration and documentation. 1639 | ▪ Knowledge on Python , Machine Learning, Deep Learning, data Science, Algorithms, Neural Network, 1640 | NLP, GCP. 1641 | ▪ Knowledge on Python Libraries like Numpy, Pandas, Seaborn , Matplotlib, Cufflinks. 1642 | ▪ Knowledge on different algorithms in Machine learning like KNN, Decision Tree, Bias variance Trade off, 1643 | Support vector Machine(SVM),Logistic Regression, Neural networks. 1644 | ▪ Have knowledge on unsupervised, Supervised and reinforcement data. 1645 | ▪ Programming experience in relational platforms like MySQL,Oracle. 1646 | ▪ Have knowledge on Some programming language like C++,Java. 1647 | ▪ Experience in cloud based environment like Google Cloud. 1648 | ▪ Working on different Operating System like Linux, Ubuntu, Windows. 1649 | ▪ Good interpersonal and communication skills. 1650 | ▪ Problem solving skills with the ability to think laterally, and to think with a medium term and long term 1651 | perspective 1652 | ▪ Flexibility and an open attitude to change. 1653 | ▪ Ability to create, define and own frameworks with a strong emphasis on code reusability. 1654 | TECHNICAL SKILLS 1655 | Programming Languages Python, C 1656 | Libraries Seaborn, Numpy, Pandas, Cufflinks, Matplotlib 1657 | Algorithms 1658 | KNN, Decision Tree, Linear regression, Logistic Regression, Neural Networks, K means clustering, 1659 | Tensorflow, SVM 1660 | Databases SQL, Oracle 1661 | Operating Systems Linux, Window 1662 | Development Environments NetBeans, Notebooks, Sublime 1663 | Ticketing tools Service Now, Remedy 1664 | Education 1665 | UG Education: 1666 | B.Tech (Computer Science) from Rayat and Bahra Institute of Engineering and Biotechnology passed with 78.4%in 1667 | 2016. 1668 | Schooling: 1669 | XII in 2012 from Moti Ram Arya Sr. Secondary School(Passed with 78.4%) 1670 | X in 2010 from Valley Public School (Passed with 9.4 CGPA) 1671 | WORK EXPERINCE 1672 | Title : Wipro Neural Intelligence Platform 1673 | Team Size : 5 1674 | Brief: Wipro’s Neural Intelligence Platform harnesses the power of automation and artificial intelligence 1675 | technologies—natural language processing (NLP), cognitive, machine learning, and analytics. The platform 1676 | comprises three layers: a data engagement platform that can easily access and manage multiple structured and 1677 | unstructured data sources; an “intent assessment and reasoning” engine that includes sentiment and predictive 1678 | analytics; and a deep machine learning engine that can sense, act, and learn over time. The project entailed 1679 | automating responses to user queries at the earliest. The Monster Bot using the power of Deep Machine Learning, 1680 | NLP to handle such queries. User can see the how their queries can be answered quickly like allL1 activities can be 1681 | eliminated. 1682 | Entity Extractor -> This involves text extraction and NLP for fetching out important information from the text like 1683 | dates, names, places, contact numbers etc. This involves Regex, Bluemix NLU api’s and machine learning using 1684 | Tensor flow for further learning of new entities. 1685 | Classifier ->This involves the classifications of classes, training of dataset and predicting the output using the SKLearn 1686 | classifier (MNB, SVM, SGD as Classifier) and SGD for the optimization to map the user queries with the best 1687 | suited response and make the system efficient. 1688 | NER: A Deep Learning NER Model is trained to extract the entities from the text. Entities like Roles, Skills, 1689 | Organizations can be extracted from raw text. RNN(LSTM) Bidirectional model is trained for extracting such entities 1690 | using Keras TensorFlow framework. 1691 | OTHER PROJECTS 1692 | Title : Diabetes Detection 1693 | Brief : Developed the software which can detect whether the person is suffering from Diabetes or not and got the third 1694 | prize in it. 1695 | TRAINING AND CERTIFICATIONS 1696 | Title: Python Training, Machine Learning, Data Science, Deep Learning 1697 | Organization: Udemy, Coursera (Machine Learning, Deep Learning) 1698 | Personal Profile 1699 | Father’s Name :Mr. Tirlok Aggarwal 1700 | Language Known : English & Hindi 1701 | Marital Status :Single 1702 | Date of Birth(Gender):1993-12-20(YYYY-MM-DD) (F) 1703 | company - Wipro 1704 | description - Developing programs in Python. 1705 | company - Wipro 1706 | description - Title : Wipro Neural Intelligence Platform 1707 | Team Size : 5 1708 | Brief: Wipro’s Neural Intelligence Platform harnesses the power of automation and artificial intelligence 1709 | technologies—natural language processing (NLP), cognitive, machine learning, and analytics. The platform 1710 | comprises three layers: a data engagement platform that can easily access and manage multiple structured and 1711 | unstructured data sources; an “intent assessment and reasoning” engine that includes sentiment and predictive 1712 | analytics; and a deep machine learning engine that can sense, act, and learn over time. The project entailed 1713 | automating responses to user queries at the earliest. The Monster Bot using the power of Deep Machine Learning, 1714 | NLP to handle such queries. User can see the how their queries can be answered quickly like allL1 activities can be 1715 | eliminated. 1716 | Entity Extractor -> This involves text extraction and NLP for fetching out important information from the text like 1717 | dates, names, places, contact numbers etc. This involves Regex, Bluemix NLU api’s and machine learning using 1718 | Tensor flow for further learning of new entities. 1719 | Classifier ->This involves the classifications of classes, training of dataset and predicting the output using the SKLearn 1720 | classifier (MNB, SVM, SGD as Classifier) and SGD for the optimization to map the user queries with the best 1721 | suited response and make the system efficient. 1722 | NER: A Deep Learning NER Model is trained to extract the entities from the text. Entities like Roles, Skills, 1723 | Organizations can be extracted from raw text. RNN(LSTM) Bidirectional model is trained for extracting such entities 1724 | using Keras TensorFlow framework. 1725 | company - Wipro Technologies 1726 | description - An IT professional with knowledge and experience of 2 years in Wipro Technologies in Machine 1727 | Learning, Deep Learning, Data Science, Python, Software Development. 1728 | ▪ Skilled in managing end-to-end development and software products / projects from inception, requirement 1729 | specs, planning, designing, implementation, configuration and documentation. 1730 | ▪ Knowledge on Python , Machine Learning, Deep Learning, data Science, Algorithms, Neural Network, 1731 | NLP, GCP. 1732 | ▪ Knowledge on Python Libraries like Numpy, Pandas, Seaborn , Matplotlib, Cufflinks. 1733 | ▪ Knowledge on different algorithms in Machine learning like KNN, Decision Tree, Bias variance Trade off, 1734 | Support vector Machine(SVM),Logistic Regression, Neural networks. 1735 | ▪ Have knowledge on unsupervised, Supervised and reinforcement data. 1736 | ▪ Programming experience in relational platforms like MySQL,Oracle. 1737 | ▪ Have knowledge on Some programming language like C++,Java. 1738 | ▪ Experience in cloud based environment like Google Cloud. 1739 | ▪ Working on different Operating System like Linux, Ubuntu, Windows. 1740 | ▪ Good interpersonal and communication skills. 1741 | ▪ Problem solving skills with the ability to think laterally, and to think with a medium term and long term 1742 | perspective 1743 | ▪ Flexibility and an open attitude to change. 1744 | ▪ Ability to create, define and own frameworks with a strong emphasis on code reusability." 1745 | C0039,"Personal Skills ➢ Ability to quickly grasp technical aspects and willingness to learn ➢ High energy levels & Result oriented. Education Details 1746 | January 2018 Master of Engineering Computer Technology & Application Bhopal, Madhya Pradesh Truba Institute of Engineering & Information Technology 1747 | January 2010 B.E. computer science Bhopal, Madhya Pradesh RKDF Institute of Science and Technology College of Engineering 1748 | January 2006 Polytechnic Information Technology Vidisha, Madhya Pradesh SATI Engineering College in Vidisha 1749 | January 2003 M.tech Thesis Detail BMCH School in Ganj basoda 1750 | Data science 1751 | 1752 | I have six month experience in Data Science. Key Skills: - Experience in Machine Learning, Deep Leaning, NLP, Python, SQL, Web Scraping Good knowledge in computer subjects and ability to update 1753 | Skill Details 1754 | Experience in Machine Learning, Deep Learning, NLP, Python, SQL, Web Crawling, HTML,CSS.- Exprience - Less than 1 year monthsCompany Details 1755 | company - RNT.AI Technology Solution 1756 | description - Text classification using Machine learning Algorithms with python. 1757 | Practical knowledge of Deep learning algorithms such as  Recurrent Neural Networks(RNN). 1758 | Develop custom data models and algorithms to apply to dataset 1759 | Experience with Python packages like Pandas, Scikit-learn, Tensor Flow, Numpy, Matplotliv, NLTK. 1760 | Comfort with SQL,  MYSQL 1761 | Sentiment analysis. 1762 |  Apply leave Dataset using classification technique like Tf--idf , LSA with cosine similarity using Machine learning Algorithms. 1763 | Web crawling using Selenium web driver and Beautiful Soup with python. 1764 | company - Life Insurance Corporation of India Bhopal 1765 | description - ü Explaining policy features and the benefits 1766 | ü Updated knowledge of life insurance products and shared with customers" 1767 | C0040,"Expertise − Data and Quantitative Analysis − Decision Analytics − Predictive Modeling − Data-Driven Personalization − KPI Dashboards − Big Data Queries and Interpretation − Data Mining and Visualization Tools − Machine Learning Algorithms − Business Intelligence (BI) − Research, Reports and Forecasts Education Details 1768 | PGP in Data Science Mumbai, Maharashtra Aegis School of data science & Business 1769 | B.E. in Electronics & Communication Electronics & Communication Indore, Madhya Pradesh IES IPS Academy 1770 | Data Scientist 1771 | 1772 | Data Scientist with PR Canada 1773 | Skill Details 1774 | Algorithms- Exprience - 6 months 1775 | BI- Exprience - 6 months 1776 | Business Intelligence- Exprience - 6 months 1777 | Machine Learning- Exprience - 24 months 1778 | Visualization- Exprience - 24 months 1779 | spark- Exprience - 24 months 1780 | python- Exprience - 36 months 1781 | tableau- Exprience - 36 months 1782 | Data Analysis- Exprience - 24 monthsCompany Details 1783 | company - Aegis school of Data Science & Business 1784 | description - Mostly working on industry project for providing solution along with Teaching Appointments: Teach undergraduate and graduate-level courses in Spark and Machine Learning as an adjunct faculty member at Aegis School of Data Science, Mumbai (2017 to Present) 1785 | company - Aegis school of Data & Business 1786 | description - Data Science Intern, Nov 2015 to Jan 2016 1787 | 1788 | Furnish executive leadership team with insights, analytics, reports and recommendations enabling effective strategic planning across all business units, distribution channels and product lines. 1789 | 1790 | ➔ Chat Bot using AWS LEX and Tensor flow Python 1791 | The goal of project creates a chat bot for an academic institution or university to handle queries related courses offered by that institute. The objective of this task is to reduce human efforts as well as reduce man made errors. Even by this companies handle their client 24x7. In this case companies are academic institutions and clients are participants or students. 1792 | ➔ Web scraping using Selenium web driver Python 1793 | The task is to scrap the data from the online messaging portal in a text format and have to find the pattern form it. 1794 | ➔ Data Visualization and Data insights Hadoop Eco System, Hive, PySpark, QlikSense 1795 | The goal of this project is to build a Business Solutions to a Internet Service Provider Company, like handling data which is generated per day basis, for that we have to visualize that data and find the usage pattern form it and have a generate a reports. 1796 | ➔ Image Based Fraud Detection Microsoft Face API, PySpark, Open CV 1797 | The main goal of project is Recognize similarity for a face to given Database images. Face recognition is the recognizing a special face from set of different faces. Face is extracted and then compared with the database Image if that Image recognized then the person already applied for loan from somewhere else and now hiding his or her identity, this is how we are going to prevent the frauds in the initial stage itself. 1798 | ➔ Churn Analysis for Internet Service Provider R, Python, Machine Learning, Hadoop 1799 | The objective is to identify the customer who is likely to churn in a given period of time; we have to pretend the customer giving incentive offers. 1800 | ➔ Sentiment Analysis Python, NLP, Apache Spark service in IBM Bluemix. 1801 | This project is highly emphasis on tweets from Twitter data were taken for mobile networks service provider to do a sentiment analysis and analyze whether the expressed opinion was positive, negative or neutral, capture the emotions of the tweets and comparative analysis. 1802 | 1803 | Quantifiable Results: 1804 | − Mentored 7-12 Data Science Enthusiast each year that have all since gone on to graduate school in Data Science and Business Analytics. 1805 | − Reviewed and evaluated 20-40 Research Papers on Data Science for one of the largest Data Science Conference called Data Science Congress by Aegis School of Business Mumbai. 1806 | − Heading a solution providing organization called Data Science Delivered into Aegis school of Data Science Mumbai and managed 4-5 live projects using Data Science techniques. 1807 | − Working for some social cause with the help of Data Science for Social Goods Committee, where our team developed a product called ""Let's find a missing Child"" for helping society. 1808 | company - IBM India pvt ltd 1809 | description - Mostly worked on blumix and IBM Watson for Data science." 1810 | , 1811 | , 1812 | , 1813 | , 1814 | , 1815 | , 1816 | , 1817 | , 1818 | , 1819 | , 1820 | , 1821 | , 1822 | , 1823 | , 1824 | , 1825 | , 1826 | , 1827 | , 1828 | , 1829 | , 1830 | , 1831 | , 1832 | , 1833 | , 1834 | , 1835 | , 1836 | , 1837 | , 1838 | , 1839 | , 1840 | , 1841 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2286 | , 2287 | , 2288 | , 2289 | , 2290 | , 2291 | , 2292 | , 2293 | , 2294 | , 2295 | , 2296 | , 2297 | , 2298 | , 2299 | , 2300 | , 2301 | , 2302 | , 2303 | , 2304 | , 2305 | , 2306 | , 2307 | , 2308 | , 2309 | , 2310 | , 2311 | , 2312 | , 2313 | , 2314 | , 2315 | , 2316 | , 2317 | , 2318 | , 2319 | , 2320 | , 2321 | , 2322 | , 2323 | , 2324 | , 2325 | , 2326 | , 2327 | , 2328 | , 2329 | , 2330 | , 2331 | , 2332 | , 2333 | , 2334 | , 2335 | , 2336 | , 2337 | , 2338 | , 2339 | , 2340 | , 2341 | , 2342 | , 2343 | , 2344 | , 2345 | , 2346 | , 2347 | , 2348 | , 2349 | , 2350 | , 2351 | , 2352 | , 2353 | , 2354 | , 2355 | , 2356 | , 2357 | , 2358 | , 2359 | , 2360 | , 2361 | , 2362 | , 2363 | , 2364 | , 2365 | , 2366 | , 2367 | , 2368 | , 2369 | , 2370 | , 2371 | , 2372 | , 2373 | , 2374 | , 2375 | , 2376 | , 2377 | , 2378 | , 2379 | , 2380 | , 2381 | , 2382 | , 2383 | , 2384 | , 2385 | , 2386 | , 2387 | , 2388 | , 2389 | , 2390 | , 2391 | , 2392 | , 2393 | , 2394 | , 2395 | , 2396 | , 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