Instructors: Petr Pošík, Jiří Spilka
Work in progress, update for the upcoming semester.
| Date | Week | Odd/Even | Contents | Link |
|---|---|---|---|---|
| 19.02.2019 | 1. | E | Course organization. Intro to Python/ML | Intro |
| 26.02.2019 | 2. | O | Bayesian and non-bayesian decision tasks | ML 1 |
| 05.03.2019 | 3. | E | Linear regression | ML 2 |
| 12.03.2019 | 4. | O | Non-linear models via basis expansion, logistic regression | ML 3 |
| 19.03.2019 | 5. | E | Model evaluation and diagnostics | ML 4 |
| 26.03.2019 | 6. | O | Decision trees and ensemble models | ML 5 |
| 02.04.2019 | 7. | E | Semestral task 1, Neural networks | ST1a, ST1b, ML 6 |
| 09.04.2019 | 8. | O | A brief intro to ST1, Bayesian networks | PM 1 |
| 16.04.2019 | 9. | E | Hidden Markov Models 1 | PM 2 |
| 23.04.2019 | 10. | O | Hidden Markov Models 2 | ST2, PM 3 |
| 30.04.2019 | 11. | E | Hierarchical Task Net (HTN) Planning | HTN |
| 07.05.2019 | 12. | O | Constraint satisfaction problems | CSP |
| 14.05.2019 | 13. | E | Schedule as on Wednesday | |
| 21.05.2019 | 14. | O | Scheduling | CPM |