Lectures
All lectures will be held on Mondays at 16:15 Liivi-202
- 08.02: Association rules and decision trees by Sven Laur
- 15.02: Linear models and polynomial interpolation by Sven Laur
- 22.02: Performance evaluation measures by Sven Laur
- 29.02: Introduction to optimization by Ilya Kuzovkin
- 07.03: Linear classification by Sven Laur
- 14.03: Neural networks by Ilya Kuzovkin
- 21.03: Basics of probabilistic modelling by Sven Laur
- 28.03: Maximum likelihood and maximum a posteriori estimates by Sven Laur
- 04.04: Principal Component Analysis by Sven Laur
- 11.04: Model-based clustering by Sven Laur
- 18.04: Expectation-maximisation algorithm by Sven Laur
- 25.04: Support Vector Machines by Sven Laur
- 02.05: Kernel Methods by Sven Laur
- 09.05: Elements of Statistical Learning Theory by Sven Laur
- 16.05: Ensemble Methods by Meelis Kull