Learn Data Analytics : Video Tutorials

★ Table of Contents ★

1) Course Introduction

2) Introduction

3) Course Overview-Part 1

4) Course Overview-Part 2

5) Graphical Approaches

6) Measures of Central Tendency

7) Measures of Dispersion

8) Random Variables and Probability Distribution

9) Probability Distributions-Part 1

10) Probability Distributions-Part 2

11) Inferential Statistics - Motivation

12) Inferential Statistics - Single sample tests

13) Two Sample tests

14) Type 1 and Type 2 Errors

15) Confidence Intervals

16) ANOVA and Test of Independence

17) Short Introduction to Regression

18) Introduction to Machine Learning

19) Supervised Learning

20) Unsupervised Learning

21) Simple and Multiple Regression

22) Regularization/ Coefficients Shrinkage

23) Data Modelling and Algorithmic Modelling

24) Ordinary Least Squares Regression

25) NPTEL MOOC IDA - Tutorial for Assignment 2

26) Training a Logistic Regression Classifier

27) Logistic Regression

28) Classification and Regression Trees-Part 1

29) Classification and Regression Trees-Part 2

30) Bias Variance Dichotomy

31) Support Vector Machines-Part 1

32) Support Vector Machines-Part 2

33) Support Vector Machines-Part 3

34) Support Vector Machines-Part 4

35) Model Assessment and Selection

36) NPTEL MOOC IDA Tutorial for Assignment 3

37) Deep Learning

38) Artificial Neural Networks-Part 1

39) Ensemble Methods and Random Forests

40) Artificial Neural Networks-Part 2

41) Associative Rule Mining-Part 1

42) Association Rule Mining-Part 2

43) Big Data, A small introduction-Part 1

44) Clustering Analysis-Part 1

45) Big Data - A small introduction-Part 2

46) Reinforcement Learning-Part 1

47) Reinforcement Learning-Part 2

48) Clustering Analysis-Part 2

49) Experimentation and Active Learning-Part 1

50) Experimentation and Active Learning-Part 2

51) Summary+ Insights into the Final Exam

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