Modules / Lectures
Module NameDownloadDescriptionDownload Size
Linear RegressionLinear AlgebraLinear Algebra Tutorial192 kb
Module NameDownloadDescriptionDownload Size
Probability TheoryAssignment 1Assignment 1 with Solutions187 kb
Probability TheoryAssignment 1Assignment 1 Questions170 kb
Linear RegressionAssignment 2Assignment2 with Solutions147 kb
Linear RegressionAssignment 2Assignment 2 Questions123 kb
Classification - Linear ModelsAssignment 3Assignment 3 with Solutions167 kb
Classification - Linear ModelsAssignment 3Assignment 3 Questions112 kb
Classification - Separating Hyperplane ApproachesAssignment 4Assignment 4 with Solutions134 kb
Classification - Separating Hyperplane ApproachesAssignment 4Assignment 4 Questions127 kb
Parameter EstimationAssignment 5Assignment 5 Questions154 kb
Parameter EstimationAssignment 5Assignment 5 Questions142 kb
Evaluation MeasuresAssignment 6Assignment 6 with Solutions259 kb
Evaluation MeasuresAssignment 6Assignment 6 Questions84 kb
Hypothesis TestingAssignment 7Assignment 7 with Solutions98 kb
Hypothesis TestingAssignment7Assignment 7 Questions53 kb
Ensemble MethodsAssignment 8Assignment 8 with Solutions57 kb
Ensemble MethodsAssignment 8Assignment 8 Questions45 kb
Graphical ModelsAssignment 9Assignment 9 with Solutions214 kb
Graphical ModelsAssignment 9Assignment 9 Questions172 kb
ClusteringAssignment 10Assignment 10 with Solutions203 kb
ClusteringAssignment 10Assignment 10 Questions188 kb
Learning TheoryAssignment 11Assignment 11 Questions118 kb
Learning TheoryAssignment 11Assignment 11 with Solutions167 kb
Reinforcement LearningAssignment 12Assignment 12 Questions61 kb
Reinforcement LearningAssignment 12Assignment 12 with Solutions81 kb


New Assignments
Module NameDownload
Week_01_Assignment_01Week_01_Assignment_01
Week_02_Assignment_02Week_02_Assignment_02
Week_03_Assignment_03Week_03_Assignment_03
Week_04_Assignment_04Week_04_Assignment_04
Week_05_Assignment_05Week_05_Assignment_05
Week_06_Assignment_06Week_06_Assignment_06
Week_07_Assignment_07Week_07_Assignment_07
Week_08_Assignment_08Week_08_Assignment_08
Week_09_Assignment_09Week_09_Assignment_09
Week_10_Assignment_10Week_10_Assignment_10
Week_11_Assignment_11Week_11_Assignment_11
Week_12_Assignment_12Week_12_Assignment_12


Sl.No Chapter Name MP4 Download Transcript Download
1A brief introduction to machine learningDownloadDownload
Verified
2Supervised LearningDownloadDownload
Verified
3Unsupervised LearningDownloadDownload
Verified
4Reinforcement LearningDownloadDownload
Verified
5Probability Basics - 1DownloadDownload
Verified
6Probability Basics - 2DownloadPDF unavailable
7Linear Algebra - 1DownloadPDF unavailable
8Linear Algebra - 2DownloadPDF unavailable
9Statistical Decision Theory - RegressionDownloadPDF unavailable
10Statistical Decision Theory - ClassificationDownloadPDF unavailable
11Bias-VarianceDownloadPDF unavailable
12Linear RegressionDownloadPDF unavailable
13Multivariate RegressionDownloadPDF unavailable
14Subset Selection 1DownloadPDF unavailable
15Subset Selection 2DownloadPDF unavailable
16Shrinkage MethodsDownloadPDF unavailable
17Principal Components RegressionDownloadPDF unavailable
18Partial Least SquaresDownloadPDF unavailable
19Linear ClassificationDownloadPDF unavailable
20Logistic RegressionDownloadPDF unavailable
21Linear Discriminant Analysis 1DownloadPDF unavailable
22Linear Discriminant Analysis 2DownloadPDF unavailable
23Linear Discriminant Analysis 3DownloadPDF unavailable
24OptimizationDownloadPDF unavailable
25Perceptron LearningDownloadPDF unavailable
26SVM - FormulationDownloadPDF unavailable
27SVM - Interpretation & AnalysisDownloadPDF unavailable
28SVMs for Linearly Non Separable DataDownloadPDF unavailable
29SVM KernelsDownloadPDF unavailable
30SVM - Hinge Loss FormulationDownloadPDF unavailable
31Weka TutorialDownloadPDF unavailable
32Early ModelsDownloadPDF unavailable
33Backpropogation IDownloadPDF unavailable
34Backpropogation IIDownloadPDF unavailable
35Initialization, Training & ValidationDownloadPDF unavailable
36Maximum Likelihood EstimateDownloadPDF unavailable
37Priors & MAP EstimateDownloadPDF unavailable
38Bayesian Parameter Estimation DownloadPDF unavailable
39IntroductionDownloadPDF unavailable
40Regression TreesDownloadPDF unavailable
41Stopping Criteria & PruningDownloadPDF unavailable
42Loss Functions for ClassificationDownloadPDF unavailable
43Categorical AttributesDownloadPDF unavailable
44Multiway SplitsDownloadPDF unavailable
45Missing Values, Imputation & Surrogate SplitsDownloadPDF unavailable
46Instability, Smoothness & Repeated SubtreesDownloadPDF unavailable
47TutorialDownloadPDF unavailable
48Evaluation Measures IDownloadPDF unavailable
49Bootstrapping & Cross ValidationDownloadPDF unavailable
502 Class Evaluation MeasuresDownloadPDF unavailable
51The ROC CurveDownloadPDF unavailable
52Minimum Description Length & Exploratory AnalysisDownloadPDF unavailable
53Introduction to Hypothesis TestingDownloadPDF unavailable
54Basic ConceptsDownloadPDF unavailable
55Sampling Distributions & the Z TestDownloadPDF unavailable
56Student\'s t-testDownloadPDF unavailable
57The Two Sample & Paired Sample t-testsDownloadPDF unavailable
58Confidence Intervals DownloadPDF unavailable
59Bagging, Committee Machines & StackingDownloadPDF unavailable
60BoostingDownloadPDF unavailable
61Gradient BoostingDownloadPDF unavailable
62Random ForestDownloadPDF unavailable
63Naive Bayes DownloadPDF unavailable
64Bayesian NetworksDownloadPDF unavailable
65Undirected Graphical Models - IntroductionDownloadPDF unavailable
66Undirected Graphical Models - Potential FunctionsDownloadPDF unavailable
67Hidden Markov ModelsDownloadPDF unavailable
68Variable EliminationDownloadPDF unavailable
69Belief PropagationDownloadPDF unavailable
70Partitional ClusteringDownloadPDF unavailable
71Hierarchical ClusteringDownloadPDF unavailable
72Threshold GraphsDownloadPDF unavailable
73The BIRCH AlgorithmDownloadPDF unavailable
74The CURE AlgorithmDownloadPDF unavailable
75Density Based ClusteringDownloadPDF unavailable
76Gaussian Mixture ModelsDownloadPDF unavailable
77Expectation MaximizationDownloadPDF unavailable
78Expectation Maximization ContinuedDownloadPDF unavailable
79Spectral ClusteringDownloadPDF unavailable
80Learning TheoryDownloadPDF unavailable
81Frequent Itemset MiningDownloadPDF unavailable
82The Apriori PropertyDownloadPDF unavailable
83Introduction to Reinforcement LearningDownloadPDF unavailable
84RL Framework and TD LearningDownloadPDF unavailable
85Solution Methods & ApplicationsDownloadPDF unavailable
86Multi-class ClassificationDownloadPDF unavailable