Modules / Lectures
Module NameDownloadDescriptionDownload Size
Week 1 - Course Overview and Descriptive StatisticsAssigment 1Assignment Questions and answers471 kb
Week 2 - Probability Distributions & Inferential StatisticsAssignment 2Assignment 2 Questions and Answers600 kb
Week 3 - Inferential StatisticsAssignment 3Assignment 3 questions and Answers466 kb
Week 4 - Machine LearningAssignment 4Assignment 4 Questions and Answers1450 kb
Week 5 - Supervised Learning (Regression and Classification Techniques) - IAssignment 5Assignment 5 Questions and Answers814 kb

Sl.No Chapter Name English
1Course OverviewDownload
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2Course Overview (cont'd)Download
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3Descriptive Statistics - Graphical ApproachesDownload
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4Descriptive Statistics - Measures of Central TendencyDownload
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5Descriptive Statistics - Measures of DispersionDownload
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6Random Variables and Probability DistributionsDownload
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7Probability Distributions(contd)Download
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8Probability Distributions(contd)Download
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9Inferential Statistics - MotivationDownload
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10Inferential Statistics - Single sample testsDownload
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11Two Sample testsDownload
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12Type 1 and Type 2 ErrorsDownload
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13Confidence IntervalsDownload
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14ANOVA and Test of IndependenceDownload
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15Short Introduction to RegressionDownload
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16Introduction to Machine LearningDownload
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17Supervised LearningDownload
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18Unsupervised LearningDownload
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19Ordinary Least Squares RegressionDownload
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20Simple and Multiple Regression in Excel and MatlabDownload
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21Regularization/ Coefficients ShrinkageDownload
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22Data Modelling and Algorithmic Modelling ApproachesDownload
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23Logistic RegressionDownload
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24Training a Logistic Regression ClassifierDownload
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25Classification and Regression TreesDownload
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26Classification and Regression Trees(contd)Download
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27Bias Variance DichotomyDownload
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28Model Assessment and SelectionDownload
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29Support Vector MachinesDownload
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30Support Vector Machines(contd)Download
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31Support Vector Machines for Non Linearly Separable DataDownload
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32Support Vector Machines and Kernel TransformationsDownload
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33Ensemble Methods and Random ForestsDownload
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34Artificial Neural NetworksDownload
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35Artificial Neural Networks(cont\'d)Download
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36Deep LearningDownload
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37Associative Rule MiningDownload
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38Association Rule Mining (contd)Download
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39Big Data, A small introductionDownload
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40Big Data - A small introduction (contd)Download
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41Clustering AnalysisDownload
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42Clustering Analysis (contd)Download
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43Introduction to Experimentation and Active LearningDownload
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44Introduction to Experimentation and Active Learning(contd)Download
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45An Introduction to Online Learning - Reinforcement LearningDownload
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46An Introduction to Online Learning - Reinforcement Learning (contd)Download
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47Summary+ Insights into the Final ExamDownload
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3GujaratiNot Available
4HindiNot Available
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7MarathiNot Available
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