Before You Submit Exercises
- Requirements to solutions of home exercises!
- Nominal score for the homework is 10 points. You can earn up to 15 points for each homework!
- Your points will appear in this table Machine Learning 2015S.
All exercise sessions will be held on Tuesdays at 16:15 Liivi-512
- 10.02: 1. GNU R and its usage given by Sven Laur
- 17.02: 3. Linear regression given by Sven Laur
- 24.02: 2. Decision trees and association rules self-study session
- 03.03: 4. Performance Measures given by Anna Leontjeva
- 10.03: 5. Optimization basics given by Konstantin Tretyakov
- 17.03: 6. Linear classification given by Sven Laur
- 24.03: 7. Neural networks given by Sven Laur
- 31.03: 8. Basics of probabilistic modelling given by Sven Laur
- 07.04: 9. Maximum likelihood and maximum a posteriori estimates given by Sven Laur
- 14.04: 10. Principle Component Analysis given by Sven Laur
- 27.04: 11. Model-based clustering given by Sven Laur
- 05.05: 12. Expectation-Maximisation algorithm given by Sven Laur
- 12.05: 13. Support Vector Machines given by Konstantin Tretyakov
- 19.05: 14. Statistical Learning Theory given by Sven Laur
- 26.05: 15. Kernel Methods given by Konstantin Tretyakov