List of competencies you should have after individual lectures. (Will be updated continuously.)
The order of lectures is subject to change.
Date | W# | Who | Contents | Materials |
---|---|---|---|---|
20.02.2018 | 1 | PP | AI, PR, learning and robotics. Decision tasks. Empirical learning. | Slides. Handouts. |
27.02.2018 | 2 | RM | Linear methods for classification and regression. | Slides. Handouts. |
06.03.2018 | 3 | PP | Non-linear models. Feature space straightening. Overfitting. | Slides. Handouts. |
13.03.2018 | 4 | PP | Nearest neighbors. Kernel functions, SVM. Decision trees. | Slides. Handouts. |
20.03.2018 | 5 | PP | Bagging. Adaboost. Random forests. | Slides. Handouts. |
27.03.2018 | 6 | PP | Neural networks. Basic models and methods, error backpropagation. | Slides. Handouts. |
03.04.2018 | 7 | PP | Deep learning. Convolutional and recurrent NNs. | Slides. Handouts. |
10.04.2018 | 8 | PP | Probabilistic graphical models. Bayesian networks. | Slides. Handouts. |
17.04.2018 | 9 | PP | Hidden Markov models. | Slides. Handouts. |
24.04.2018 | 10 | PP | Expectation-Maximization algorithm. | Slides. Handouts. |
01.05.2018 | 11 | No lecture. Public holiday. | ||
08.05.2018 | 12 | No lecture. Public holiday. | ||
15.05.2018 | 13 | RM | Planning. Planning problem representations. Planning methods. | Handouts |
17.05.2018 | 13 | RM | Schedule as on Tuesday. Constraint satisfaction problems. | Handouts |
22.05.2018 | 14 | RM | Scheduling. Local search. | Handouts |