Lecture notes/slides will be uploaded during the course.

Download Textbook lecture notes

VideoLectures Online video on RL

Please download the above textbook slides. My slides are based on theirs with minor modification

Chapter 1. Introduction (ppt) Chapter 2. Supervised Learning (ppt) Chapter 3. Bayesian Decision Theory (ppt) Chapter 4. Parametric Methods (ppt) Chapter 5. Multivariate Methods (ppt) Chapter 6. Dimensionality Reduction (ppt) Chapter 7. Clustering (ppt) Chapter 8. Nonparametric Methods (ppt) Chapter 9. Decision Trees (ppt) Chapter 10. Linear Discrimination (ppt) Chapter 11. Multilayer Perceptrons (ppt) Chapter 12. Local Models (ppt) Chapter 13. Hidden Markov Models (ppt) Chapter 14. Assessing and Comparing Classification Algorithms (ppt) Chapter 15. Combining Multiple Learners (ppt) Chapter 16. Reinforcement Learning (ppt)

Week 1 (Chapter 1)

chapter1.ppt

Week 2 (Chapter 2)

chapter2.ppt

Week 3

lec3.ppt

Week 4

lec4.ppt

Week 5

lec5.ppt

lec6.ppt

Week 6

lec7.ppt

lec8.ppt

Week7

lec9.ppt Linear discriminant

Week8

lec10.ppt Neural networks

Week9

lec11.ppt GA, GP

Week10

Midterm March 15.

Week11

lec13.ppt SVM

Week12

lec14.ppt evaluation of classifers

Week13

lec15.ppt HMM

HMM1.ppt

HMM2.ppt

Week14

DimRed.ppt dimension reduction

ensemble.ppt Ensemble Learning Algorithms

Week15

lec17.ppt Reinforcement Learning

Richard Sutton's Talk on RL

Week16

lec18.ppt Graphical models