Course slides are available on Moodle.
Date  Topics  Reading 

18/07/2011 
Overview of the course

Lecture slides
Chapter 1 of SS17 
20/07/2011 
Classification

Slides 
20/07/2018  03/08/2018 
Decision tree classification,

slides
Chapter 3 of Mitchell97 
27/7/2018 
Quiz 1,

Sample reading: sections 3.1 to 3.9 here 
01/08/2018  17/08/2018 
Probabilistic classifiers

Chapters 4.2, 4.3.2 of Bis07
Example: naive Bayes Lecture notes PDF and OneNote Link Additional reading: Mitchell's chapter 
17/8/2018 
Quiz 2, Probabilistic classifiers 

24/08/2018

Hyperplane classifiers,

Lecture notes 
29/08/2018, 31/08/2018

Convex Optimization (Review),

Convex functions notes Optimization notes 
06/09/2018, 19/09/2018, 26/09/2018 
Feedforward Neural networks ,

Lecture slides, Slides as pdf Chapter 6 of Deep Learning book 
28/09/2018 
Convolutional Neural Networks 

03/10/2018, 05/10/2018, 10/10/2018 
Recurrent Neural Networks 
Lecture slides Slides in pdf Chapter 10.0 to 10.4 of Deep Learning book 
10/10/2018, 12/10/2018, 17/10/2018 
Clustering

Lecture notes 
24/10/2018, 26/10/2018 
Combining models

Lecture notes: bagging Lecture notes: boosting 
31/10/2018, 02/10/2018 
Support vector machines (Chapter 7 of Bis07)

Lecture notes Wikipedia 
07/11/2018 
Overview of graphical models  
09/11/2018

Overview of Markov Decision Process and Reinforcement Learning Lecture by Sabyasachi Ghosh
