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  • Tuesdays, 12:45-14:15, KN:E-126
  • Lecturers: Petr Pošík (PP), Radek Mařík (RM)

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
courses/ui/lectures.txt · Last modified: 2018/05/15 10:02 by spilkjir