OUTLINE OF THE COURSE (click on the link to watch the video of the lecture)

1. Overview

2. Statistics for Machine Learning

3. Overfitting control (cross-validation, regularization methods, ...)

4. Bayesian Learning

5. Classification and Decision Trees (also here)

6. Neural networks

7. Non-parametric methods

8. Unsupervised Learning