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
|