Textbooks: Pattern Recognition and Machine Learning by Bishop (PRML)
and The Elements of Statistical Learning by Hastie, Tibshirani, and Friedman (ESL)
(both are optional)
Lecture outline:
| Topic | PRML Chapter | ESL Chapter | # of lectures |
| Problem Setup | 1 | 1 | 1 |
| Linear Regression | 3 | 3 | 2 |
| Linear Classification | 4 | 4 | 3 |
| Nearest-Neighbor | 13 | 1 | |
| Neural Networks | 5 | 11 | 2 |
| RBF, Gaussian Processes | 6 | 6 | 3 |
| SVM | 7 | 12 | 2 |
| Boosting | 14 | 10 | 3 |