COURSE OUTLINESession 1
Introduction
Session 2
Decision trees
Session 3
Theory of learning-1
PAC-learning
Session 4
Linear models
Session 5
Theory of learning-2
VC-dimension
Session 7-8
Support vector machines
Session 9
Artificial neural networks
Session 10-11
Deep neural networks
Session 12
Compositions
Session 13-14
Boosting
Session 15
Practical machine learning
Session 6
Regularisation