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Lectures

  • Tuesdays, 12:45-14:15, KN:E-301
  • 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
19.02.2019 1 PP AI, PR, learning and robotics. Decision tasks. Empirical learning. Slides. Handouts.
26.02.2019 2 PP Linear methods for classification and regression. Slides. Handouts.
05.03.2019 3 RM Non-linear models. Feature space straightening. Overfitting. Slides. Handouts.
12.03.2019 4 PP Nearest neighbors. Kernel functions, SVM. Decision trees. Slides. Handouts.
19.03.2019 5 PP Bagging. Adaboost. Random forests. Slides. Handouts.
26.03.2019 6 PP Neural networks. Basic models and methods, error backpropagation. Slides. Handouts.
02.04.2019 7 PP Deep learning. Convolutional and recurrent NNs. Slides. Handouts.
09.04.2019 8 PP Probabilistic graphical models. Bayesian networks. Slides. Handouts.
16.04.2019 9 PP Hidden Markov models. Slides. Handouts.
23.04.2019 10 PP Expectation-Maximization algorithm. Slides. Handouts.
30.04.2019 11 RM Planning. Planning problem representations. Planning methods. Handouts
07.05.2019 12 RM Constraint satisfaction problems. Handouts
14.05.2019 13 No lecture. Schedule as on wednesday.
21.05.2019 14 RM Scheduling. Local search. Handouts
courses/ui/lectures.txt · Last modified: 2019/02/18 14:52 by spilkjir