Saradhi

Assistant Professor
Department of Computer Science and Engineering
IIT Guwahati

CS562: Machine Learning:

1. Introduction
2. Decision Trees
3. Probability Primer
4. Bayes Decision Theory
5. Maximum-likelihood and Bayesian Parameter Estimation
6. Non-parametric Techniques
7. Bayes Networks
8. Optimization Primer
9. Linear Discriminant Functions
10. Support Vector Machines
11. Unsupervised Learning
12. Semi Supervised Learning
13. Reinforcement Learning

1. Pattern Classification , Richard O. Duda, Peter E. Hart and David G. Strok, 2nd Edition, Wiley Interscience
2. Pattern Recognition , Sergios Theodoridis and Koutroumbas, Academic Press, Third Edition
3. Machine Learning , Tom M. Mitchell, McGrahill International Editions