├── Day 1.md ├── Day 10.md ├── Day 2.md ├── Day 3.md ├── Day 4.md ├── Day 5.md ├── Day 6.md ├── Day 7.md ├── Day 8.md ├── Day 9.md └── README.md /Day 1.md: -------------------------------------------------------------------------------- 1 | # Day 1 2 | ## Measures of Central Tendency:- 3 | **Article:** https://statistics.laerd.com/statistical-guides/measures-central-tendency-mean-mode-median.php \ 4 | **FAQ:** https://statistics.laerd.com/statistical-guides/measures-central-tendency-mean-mode-median-faqs.php \ 5 | **Short Questions:** https://itfeature.com/short-question/Measure%20of%20Central%20Tendency.html#sthash.5yaJdevE.dpbs \ 6 | **Video(Might wanna turn the speed to .75x):** https://www.youtube.com/watch?v=kn83BA7cRNM&list=PL8dPuuaLjXtNM_Y-bUAhblSAdWRnmBUcr&index=4&ab_channel=CrashCourse 7 | 8 | ## Population and Sample:- 9 | **Article with Fancy Terms:** https://sanjayjsw05.medium.com/population-and-sample-in-data-science-and-statistics-8a6d67e2f450 \ 10 | **Population and Sample Overview:** https://www.youtube.com/watch?v=iUutXUIwAvw&list=PLZoTAELRMXVMhVyr3Ri9IQ-t5QPBtxzJO&index=7&ab_channel=KrishNaik 11 | 12 | ## Sampling Methods(Optional):- 13 | **Part 1(Probabilistic Sampling):** https://sanjayjsw05.medium.com/sampling-in-statistical-research-part-1-9321a23071cc \ 14 | **Part 2(Non Probabilistic Sampling):** https://sanjayjsw05.medium.com/sampling-in-statistical-research-part-2-7bb830898fb2 15 | 16 | ## Probability:- 17 | **Basics:** https://ltcconline.net/greenl/courses/102/Probability/basic_terms_of_probability.htm \ 18 | **Random Variable:** https://towardsdatascience.com/understanding-random-variable-a618a2e99b93 \ 19 | **Conditional Probability and Total Probability Theorem:** https://corporatefinanceinstitute.com/resources/knowledge/other/total-probability-rule/#:~:text=However%2C%20we%20know%20the%20probability,the%20probability%20of%20event%20A. \ 20 | **Bayes Theorem(Simplest Case):** https://www.youtube.com/watch?v=XQoLVl31ZfQ&t=14s&ab_channel=Dr.TreforBazett \ 21 | **Bayes Theorem(Generalized):** https://www.youtube.com/watch?v=k6Dw0on6NtM&ab_channel=Dr.TreforBazett \ 22 | **Bayes Theorem(Optional since it might get a bit confusing but it's still the best):** https://www.youtube.com/watch?v=HZGCoVF3YvM&ab_channel=3Blue1Brown 23 | -------------------------------------------------------------------------------- /Day 10.md: -------------------------------------------------------------------------------- 1 | # Day 10 2 | **All in One:** https://stats.idre.ucla.edu/spss/seminars/introduction-to-factor-analysis/a-practical-introduction-to-factor-analysis/ \ 3 | **Code Guided Article:** https://www.datacamp.com/community/tutorials/introduction-factor-analysis 4 | -------------------------------------------------------------------------------- /Day 2.md: -------------------------------------------------------------------------------- 1 | # Day 2 2 | ## Types of Data:- 3 | **Article:** https://statistics.laerd.com/statistical-guides/types-of-variable.php \ 4 | **More Elaborate One:** https://towardsdatascience.com/data-types-in-statistics-347e152e8bee 5 | 6 | ## Measures of Dispersion:- 7 | **Article:** https://byjus.com/commerce/measures-of-dispersion/ \ 8 | **Article(With EXCEL Demo):** https://medium.com/analytics-vidhya/calculating-measure-of-dispersion-da8e9fa7ef83 \ 9 | **Video:** https://www.youtube.com/watch?v=SzZ6GpcfoQY&ab_channel=StatQuestwithJoshStarmer 10 | 11 | ## Data Vizualization:- 12 | **One for All Article:** https://www.klipfolio.com/resources/articles/what-is-data-visualization \ 13 | **Finding Correct Bin Size:** https://www.statisticshowto.com/choose-bin-sizes-statistics/ 14 | 15 | ## Data Distribution:- 16 | **What is Statistical Distribution:** https://www.youtube.com/watch?v=oI3hZJqXJuc&t=202s&ab_channel=StatQuestwithJoshStarmer \ 17 | **Normal Distribution:** https://www.youtube.com/watch?v=rzFX5NWojp0&ab_channel=StatQuestwithJoshStarmer \ 18 | **Normal Distribution - II:** https://www.youtube.com/watch?v=rBjft49MAO8&ab_channel=CrashCourse \ 19 | **Normal Distribution - III:** https://www.youtube.com/watch?v=mtbJbDwqWLE&ab_channel=SimpleLearningPro \ 20 | \ 21 | **Norm. Dist. Article:** https://www.scribbr.com/statistics/normal-distribution/ \ 22 | **Standard Normal Distribution:** https://www.scribbr.com/statistics/standard-normal-distribution/ \ 23 | **t Distribution:** https://www.scribbr.com/statistics/t-distribution/ \ 24 | \ 25 | **Central Limit Theorem Intuition:** https://www.youtube.com/watch?v=YAlJCEDH2uY&ab_channel=StatQuestwithJoshStarmer \ 26 | **CLT Math:** https://www.youtube.com/watch?v=PUBZC2MJ50Y&ab_channel=KrishNaik \ 27 | **CLT Bazinga:** https://www.youtube.com/watch?v=JNm3M9cqWyc&ab_channel=KhanAcademy \ 28 | **Sampling Distribution:** https://www.statisticshowto.com/sampling-distribution/ 29 | -------------------------------------------------------------------------------- /Day 3.md: -------------------------------------------------------------------------------- 1 | # Day 3 2 | ## Confidence Intervals:- 3 | **Standard Error:** https://www.scribbr.com/statistics/standard-error/ \ 4 | **Article:** https://towardsdatascience.com/a-very-friendly-introduction-to-confidence-intervals-9add126e714 \ 5 | **Calculate CI:** https://www.statisticshowto.com/probability-and-statistics/confidence-interval/ \ 6 | **CI Visualizer:** https://rpsychologist.com/d3/ci/ \ 7 | **Video 1:** https://www.youtube.com/watch?v=TqOeMYtOc1w&ab_channel=StatQuestwithJoshStarmer \ 8 | **Video 2(A Bit Long):** https://www.youtube.com/watch?v=EJe3jiZNwUU&ab_channel=zedstatistics 9 | 10 | ## Maximum Likelihood Estimation:- 11 | **Probability vs Likelihood:** https://www.youtube.com/watch?v=pYxNSUDSFH4&ab_channel=StatQuestwithJoshStarmer \ 12 | **Maximum Likelihood Estimation Steps:** https://www.youtube.com/watch?v=XepXtl9YKwc&ab_channel=StatQuestwithJoshStarmer \ 13 | **Maximum Likelihood Estimation Example:** https://www.youtube.com/watch?v=Dn6b9fCIUpM&ab_channel=StatQuestwithJoshStarmer 14 | 15 | ## How to Handle Outliers? 16 | **Fantastic Outliers and Where to Find them:** https://www.statisticshowto.com/find-outliers/ \ 17 | **How to deal with them:** https://www.kdnuggets.com/2017/01/3-methods-deal-outliers.html \ 18 | **Another One:** https://www.rapidinsight.com/blog/handle-outliers/ \ 19 | **Code Walkthrough:** https://medium.com/analytics-vidhya/outlier-treatment-9bbe87384d02 20 | 21 | ## Z-Score:- 22 | **Full Guide:** https://www.statisticshowto.com/probability-and-statistics/z-score/ \ 23 | **Questions Walkthrough:** https://statistics.laerd.com/statistical-guides/standard-score.php \ 24 | **Video:** https://www.youtube.com/watch?v=4Fta6KQ1QHQ&ab_channel=KrishNaik 25 | 26 | ## PDF and CDF:- 27 | **Quick Overview:** https://medium.com/analytics-vidhya/pdf-pmf-and-cdf-in-machine-learning-225b41242abe \ 28 | **Questions:** https://www.probabilitycourse.com/chapter4/4_1_3_functions_continuous_var.php \ 29 | **Video:** https://www.youtube.com/watch?v=YXLVjCKVP7U&ab_channel=zedstatistics \ 30 | **Code Video:** https://www.youtube.com/watch?v=HHiC5OaXNLY&ab_channel=LazyProgrammer 31 | 32 | ## Kernel Density Estimation:- 33 | **Interactive Blog:** https://mathisonian.github.io/kde/ 34 | **Article:** https://medium.com/analytics-vidhya/kernel-density-estimation-kernel-construction-and-bandwidth-optimization-using-maximum-b1dfce127073 \ 35 | **Article - 2:** https://towardsdatascience.com/histograms-vs-kdes-explained-ed62e7753f12 \ 36 | **In-depth Blog:** https://machinelearningmastery.com/probability-density-estimation/ \ 37 | **Video:** https://www.youtube.com/watch?v=PUvUQMQ7xQk&ab_channel=KhanAcademy \ 38 | **Code:** https://seaborn.pydata.org/tutorial/distributions.html#kernel-density-estimation \ 39 | **Real-Life Scenario:** https://towardsdatascience.com/how-twitter-and-machine-learning-kde-lda-help-to-predict-crime-5b8abbd15596 40 | 41 | ## Moments and their Significance:- 42 | **Article:** https://medium.com/analytics-vidhya/statistics-moments-of-a-distribution-1bcfc4cbbd48 \ 43 | **Video:** https://www.youtube.com/watch?v=TM033GCU-SY&ab_channel=zedstatistics 44 | -------------------------------------------------------------------------------- /Day 4.md: -------------------------------------------------------------------------------- 1 | # Day 4 2 | ## Covariance:- 3 | **Article:** https://www.statisticshowto.com/covariance/ \ 4 | **Covariance Video:** https://www.youtube.com/watch?v=qtaqvPAeEJY&ab_channel=StatQuestwithJoshStarmer \ 5 | **Covariance Matrix:** https://www.youtube.com/watch?v=152tSYtiQbw&ab_channel=ritvikmath \ 6 | **np.cov() Doc:** https://numpy.org/doc/stable/reference/generated/numpy.cov.html 7 | 8 | ## Correlation:- 9 | **Ful Correlation(Pearson Coefficient):** https://www.youtube.com/watch?v=xZ_z8KWkhXE&ab_channel=StatQuestwithJoshStarmer \ 10 | **R-squared(Optional):** https://www.youtube.com/watch?v=2AQKmw14mHM&ab_channel=StatQuestwithJoshStarmer \ 11 | **Spearman Rank Coefficient:** https://www.statisticshowto.com/spearman-rank-correlation-definition-calculate/ \ 12 | **Uses, Limitation and Corr vs Causation:** https://www.simplypsychology.org/correlation.html \ 13 | **Correlation vs Causation:** https://www.youtube.com/watch?v=X42aAg32rhk&ab_channel=Udacity \ 14 | **scipy.stats.pearsonr Doc:** https://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.stats.pearsonr.html \ 15 | **scipy.stats.spearmanr Doc:** https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.spearmanr.html 16 | 17 | ## Test of Normality:- 18 | **QQ Plot:** https://www.youtube.com/watch?v=okjYjClSjOg&ab_channel=StatQuestwithJoshStarmer \ 19 | **Shapiro Wilk Test:** https://www.youtube.com/watch?v=dRAqSsgkCUc&ab_channel=MatthewE.Clapham \ 20 | **Kolmogorov Smirnov Test:** https://www.statisticshowto.com/kolmogorov-smirnov-test/ \ 21 | **KS Test Video:** https://www.youtube.com/watch?v=ZO2RmSkXK3c&ab_channel=MatthewE.Clapham \ 22 | **Lilliefors Test:** https://www.statisticshowto.com/lilliefors-test/ \ 23 | **One for All Code Guide:** https://towardsdatascience.com/6-ways-to-test-for-a-normal-distribution-which-one-to-use-9dcf47d8fa93 24 | 25 | ## Anscombe's Quartet: 26 | **Article:** https://medium.com/datadriveninvestor/anscombes-quartet-12649db7eac0 \ 27 | **Article 2:** https://heap.io/blog/data-stories/anscombes-quartet-and-why-summary-statistics-dont-tell-the-whole-story \ 28 | **Video:** https://www.youtube.com/watch?v=sfH43temzQY&ab_channel=jbstatistics 29 | -------------------------------------------------------------------------------- /Day 5.md: -------------------------------------------------------------------------------- 1 | # Day 5 2 | ## Chebyshev's Inequality:- 3 | **Article**: https://medium.com/analytics-vidhya/chebyshevs-inequality-66cce7067a70 \ 4 | **Video**: https://www.youtube.com/watch?v=DWsDqKlW7Z4&ab_channel=KrishNaik 5 | 6 | ## Hypothesis Testing:- 7 | **Hypothesis Testing and Null Hypothesis**: https://www.youtube.com/watch?v=0oc49DyA3hU&ab_channel=StatQuestwithJoshStarmer \ 8 | **Alternative Hypothesis**: https://www.youtube.com/watch?v=5koKb5B_YWo&ab_channel=StatQuestwithJoshStarmer \ 9 | **p-values Intro**: https://www.youtube.com/watch?v=vemZtEM63GY&t=2s&ab_channel=StatQuestwithJoshStarmer \ 10 | **How to Calculate p-values**: https://www.youtube.com/watch?v=JQc3yx0-Q9E&t=20s&ab_channel=StatQuestwithJoshStarmer \ 11 | **Hypo. Tests in One Picture**: https://www.datasciencecentral.com/profiles/blogs/hypothesis-tests-in-one-picture \ 12 | **p-hacking**: https://www.youtube.com/watch?v=HDCOUXE3HMM&ab_channel=StatQuestwithJoshStarmer \ 13 | **All about Hypothesis Testing**: https://www.youtube.com/watch?v=8JIe_cz6qGA&ab_channel=zedstatistics 14 | 15 | ## Chi-Square Test:- 16 | **Article**: https://www.statisticshowto.com/probability-and-statistics/chi-square/#chisquarep \ 17 | **Fundamentals**: https://medium.com/@nhan.tran/the-chi-square-statistic-p-1-37a8eb2f27bb \ 18 | **Chi Square for Independence**: https://www.youtube.com/watch?v=NTHA9Qa81R8&ab_channel=zedstatistics \ 19 | **Chi Square for Goodness of Fit**: https://www.youtube.com/watch?v=ZNXso_riZag&ab_channel=zedstatistics \ 20 | **Python Implementation**: https://towardsdatascience.com/chi-squared-test-for-feature-selection-with-implementation-in-python-65b4ae7696db 21 | 22 | ## t-Tests:- 23 | **T-tests Article**: https://www.scribbr.com/statistics/t-test/ \ 24 | **Another one**: https://medium.com/@sbjeetmeet11/hypothesis-testing-ii-using-t-tests-4f6967046951 \ 25 | **Video(Skip ANOVA for now)**: https://www.youtube.com/watch?v=NF5_btOaCig&ab_channel=StatQuestwithJoshStarmer \ 26 | **Chi Square and t Test Combined**: https://www.youtube.com/watch?v=I10q6fjPxJ0&ab_channel=GlobalHealthwithGregMartin \ 27 | **Python Implementation**: https://machinelearningmastery.com/how-to-code-the-students-t-test-from-scratch-in-python/ 28 | 29 | ## Statistical Power and Power Analysis:- 30 | **Statistical Power**: https://www.youtube.com/watch?v=Rsc5znwR5FA&ab_channel=StatQuestwithJoshStarmer \ 31 | **Power Analysis**: https://www.youtube.com/watch?v=VX_M3tIyiYk&ab_channel=StatQuestwithJoshStarmer \ 32 | **Power Analysis in Python**: https://towardsdatascience.com/introduction-to-power-analysis-in-python-e7b748dfa26 33 | 34 | ## More on Distribution(Optional):- 35 | ### Discrete and Continuous Distributions:- 36 | **What are They?**: https://www.youtube.com/watch?v=QRen4oqu56Y&ab_channel=yaymath \ 37 | **Calculating for Cont. Dist.**: https://www.youtube.com/watch?v=EPm7FdajBvc&ab_channel=jbstatistics 38 | 39 | ### Bernoulli's and Binomial Distrbution:- 40 | **Article**: https://www.statisticshowto.com/probability-and-statistics/binomial-theorem/binomial-distribution-formula/ \ 41 | **Binomial Distribution**: https://www.youtube.com/watch?v=J8jNoF-K8E8&ab_channel=StatQuestwithJoshStarmer \ 42 | **Bernoulli Distribution**: https://www.youtube.com/watch?v=bT1p5tJwn_0&ab_channel=jbstatistics 43 | 44 | ### Poisson Distribution:- 45 | **Video**: https://www.youtube.com/watch?v=BbLfV0wOeyc&ab_channel=365DataScience \ 46 | **Video I**: https://www.youtube.com/watch?v=cPOChr_kuQs&ab_channel=zedstatistics 47 | 48 | ### Non-Normal Distribution Overview:- 49 | **Video**: https://www.statisticshowto.com/probability-and-statistics/non-normal-distributions/ \ 50 | **Video-II**: https://www.youtube.com/watch?v=MbPARxESHUc&ab_channel=ResearchByDesign 51 | -------------------------------------------------------------------------------- /Day 6.md: -------------------------------------------------------------------------------- 1 | # Day 6 2 | ## Scipy Tutorial:- 3 | **Git Repo:** https://github.com/AllenDowney/CompStats \ 4 | **Binder:** https://mybinder.org/v2/gh/allendowney/compstats/master \ 5 | **Site Tutorial:** https://allendowney.github.io/CompStats/tutorial \ 6 | **OP Talk:** https://www.youtube.com/watch?v=He9MCbs1wgE&ab_channel=Enthought 7 | 8 | ## ANOVA:- 9 | **Dive In:** https://medium.com/@StepUpAnalytics/anova-one-way-vs-two-way-6b3ff87d3a94 \ 10 | **Code Article:** https://www.analyticsvidhya.com/blog/2020/06/introduction-anova-statistics-data-science-covid-python/ \ 11 | **Video: https:** //www.youtube.com/watch?v=YrhlQB3mQFI&ab_channel=KrishNaik \ 12 | **Statquest:** https://www.youtube.com/watch?v=NF5_btOaCig&t=3s&ab_channel=StatQuestwithJoshStarmer 13 | 14 | ## Feature Scaling:- 15 | **Min-Max Scaling:** https://towardsdatascience.com/everything-you-need-to-know-about-min-max-normalization-in-python-b79592732b79 \ 16 | **Normal Distribution:** https://medium.com/fintechexplained/ever-wondered-why-normal-distribution-is-so-important-110a482abee3 \ 17 | **Imp. of Normal Dist.:** https://people.richland.edu/james/lecture/m113/normal_important.html \ 18 | **Imp. of Normal Dist. II:** https://towardsdatascience.com/why-data-scientists-love-gaussian-6e7a7b726859 \ 19 | **Imp. of Normal Dist. III:** https://www.quora.com/Why-is-the-normal-distribution-important \ 20 | **Standard Scaling:** https://towardsdatascience.com/how-and-why-to-standardize-your-data-996926c2c832 \ 21 | **Standardization Vs Normalization:** https://www.analyticsvidhya.com/blog/2020/04/feature-scaling-machine-learning-normalization-standardization/ \ 22 | **Standardization Vs Normalization - II:** https://www.youtube.com/watch?v=mnKm3YP56PY&ab_channel=KrishNaik \ 23 | **All About Scaling:** https://towardsdatascience.com/all-about-feature-scaling-bcc0ad75cb35 24 | -------------------------------------------------------------------------------- /Day 7.md: -------------------------------------------------------------------------------- 1 | # Day 7 2 | ## Feature Encodings:- 3 | **Article:** https://www.geeksforgeeks.org/feature-encoding-techniques-machine-learning/ \ 4 | **Article II:** https://towardsdatascience.com/all-about-categorical-variable-encoding-305f3361fd02 \ 5 | **Video:** https://www.youtube.com/watch?v=OTPz5plKb40&ab_channel=KrishNaik 6 | 7 | ## Handling Skewed Data:- 8 | **Article:** https://towardsdatascience.com/top-3-methods-for-handling-skewed-data-1334e0debf45 \ 9 | **Article II:** https://towardsdatascience.com/transforming-skewed-data-73da4c2d0d16 \ 10 | **Math behind Box-Cox:** https://www.statisticshowto.com/box-cox-transformation/ 11 | 12 | ## Handling Missing Data:- 13 | **Article:** https://analyticsindiamag.com/5-ways-handle-missing-values-machine-learning-datasets/ \ 14 | **Article - II:** https://towardsdatascience.com/how-to-handle-missing-data-8646b18db0d4 \ 15 | **Article - III:** https://dev.acquia.com/blog/how-to-handle-missing-data-in-machine-learning-5-techniques/09/07/2018/19651 \ 16 | **Video:** https://www.youtube.com/watch?v=S6hcGwhNbIM&ab_channel=KrishNaik \ 17 | **Missing Values in Time Series Data Code:** https://www.kaggle.com/juejuewang/handle-missing-values-in-time-series-for-beginners \ 18 | **Missing Values in Time Series Data:** https://www.youtube.com/watch?v=GEytNZVjZNU&ab_channel=AIEngineering 19 | -------------------------------------------------------------------------------- /Day 8.md: -------------------------------------------------------------------------------- 1 | # Day 8 2 | ## Handling Class Imbalance:- 3 | **All in One:** https://www.analyticsvidhya.com/blog/2017/03/imbalanced-data-classification/ 4 | 5 | ## Using Metrics:- 6 | **Confusion Matrix Video:** https://www.youtube.com/watch?v=Kdsp6soqA7o&ab_channel=StatQuestwithJoshStarmer \ 7 | **Sensitivity and Specificity Video:** https://www.youtube.com/watch?v=vP06aMoz4v8&ab_channel=StatQuestwithJoshStarmer \ 8 | **All About Metrics:** https://medium.com/analytics-vidhya/confusion-matrix-accuracy-precision-recall-f1-score-ade299cf63cd \ 9 | **AUC-ROC Curve:** https://www.youtube.com/watch?v=4jRBRDbJemM&ab_channel=StatQuestwithJoshStarmer \ 10 | **MCC:** https://towardsdatascience.com/the-best-classification-metric-youve-never-heard-of-the-matthews-correlation-coefficient-3bf50a2f3e9a 11 | 12 | ## Resampling Techniques:- 13 | **Random Under-Sampling and Random Over-Sampling:** https://machinelearningmastery.com/random-oversampling-and-undersampling-for-imbalanced-classification/ \ 14 | **SMOTE:** https://towardsdatascience.com/5-smote-techniques-for-oversampling-your-imbalance-data-b8155bdbe2b5 \ 15 | **ADASYN:** https://towardsdatascience.com/adasyn-adaptive-synthetic-sampling-method-for-imbalanced-data-602a3673ba16 \ 16 | **Types of SMOTE Techniques:** https://towardsdatascience.com/5-smote-techniques-for-oversampling-your-imbalance-data-b8155bdbe2b5 \ 17 | **SMOTE Video:** https://www.youtube.com/watch?v=U3X98xZ4_no&ab_channel=BhaveshBhatt 18 | -------------------------------------------------------------------------------- /Day 9.md: -------------------------------------------------------------------------------- 1 | # Day 9 2 | ## Articles:- 3 | **Introduction:** https://heartbeat.fritz.ai/hands-on-with-feature-selection-techniques-an-introduction-1d8dc6d86c16 \ 4 | **Filter Methods:** https://heartbeat.fritz.ai/hands-on-with-feature-selection-techniques-filter-methods-f248e0436ce5 \ 5 | **Wrapper Methods:** https://heartbeat.fritz.ai/hands-on-with-feature-selection-techniques-wrapper-methods-5bb6d99b1274 \ 6 | **Embedded Methods:** https://heartbeat.fritz.ai/hands-on-with-feature-selection-techniques-embedded-methods-84747e814dab \ 7 | **Hybrid Methods:** https://heartbeat.fritz.ai/hands-on-with-feature-selection-techniques-hybrid-methods-b93b1b06d3a5 \ 8 | **Advanced Methods:** https://heartbeat.fritz.ai/hands-on-with-feature-selection-techniques-more-advanced-methods-234f2e501be7 \ 9 | **All in One:** https://www.analyticsvidhya.com/blog/2020/10/feature-selection-techniques-in-machine-learning/ \ 10 | **Sum it up:** https://towardsdatascience.com/the-5-feature-selection-algorithms-every-data-scientist-need-to-know-3a6b566efd2 11 | 12 | ## Video:- 13 | **Krish Sir:** https://www.youtube.com/watch?v=k-EpAMjw6AE&ab_channel=KrishNaik \ 14 | **Data School:** https: //www.youtube.com/watch?v=YaKMeAlHgqQ&ab_channel=DataSchool \ 15 | **Dimensionality Reduction Talk:** https://www.youtube.com/watch?v=ioXKxulmwVQ&ab_channel=PyData 16 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # 10-Days-of-Statistics-and-Data-Preprocessing 2 | List of all the resources I used during 10 days of Statistics and Data Preprocessing. \ 3 | **Mind Map Link:** https://whimsical.com/10-days-of-statistics-and-data-preprocessing-J6LrtgbUR1mur4kSBJcYLU@2Ux7TurymMMmZfJy3KTg \ 4 | ![10 Days Of Statistics and Data Preprocessing (1)](https://user-images.githubusercontent.com/43719685/103491151-53c50f00-4e47-11eb-9539-75c6a488467a.png) 5 | 6 | --------------------------------------------------------------------------------