
Topic 
Slides 
Required Reading 
Optional Reading 

Introduction 
ppt
pdf

Ch.1 from I2ML 


Supervised Learning 
ppt
pdf

Ch.2 from I2ML 


Linear Classifiers I 
ppt
pdf

Andrew Ng's notes:



Linear Classifiers II 
ppt
pdf




Decision Trees 
ppt
pdf

Read any one of the following:

Ch. 9.19.4 from I2ML

Ch. 3 from ML

Ch. 8.28.4 from DHS



NonParametric Classifiers 
ppt
pdf

Read any one of the following:

Ch. 8 from I2ML

Ch. 4.44.6 from DHS

Ch. 4.44.6 from DHS



Evaluation 
ppt
pdf




Support Vector Machines 
ppt
pdf

Read any one of the following:



BiasVariance Tradeoff 
ppt
pdf




Bayesian Learning 
ppt
pdf




Neural Networks 
pdf 



Clustering I 
ppt
pdf

Read material from any one of I2ML or HMS:

Sec. 9.6, 6.4, 7.3.2, 7.4 and 8.4 from HMS

Ch. 7 from I2ML



Clustering II 
ppt
pdf

Andrew Ng's notes:

Optional reading:


Spectral Clustering 
ppt
pdf 


Bayes nets: Representation 
ppt
pdf




Bayes nets: Inference 
ppt
pdf

Please read the following:
 Chapter 7 from BNB
 Sections 8.1,8.2,8.3 and 8.7 from BNB



Bayes nets: Learning 
ppt
pdf

Please read Chapter 15 from BNB 
Optional reading: Tutorial on Learning with Bayes nets


Hidden Markov Models 
ppt
pdf

HMM notes



Reinforcement Learning 
ppt
pdf

Read any one of:



Wrap up 
ppt
pdf



