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This course introduces statistical decision theory and surveys canonical and advanced classifiers such as perceptrons, AdaBoost, support vector machines, and neural nets.
Winter semester 2023/2024
Teaching: Jiří Matas (JM) matas@cmp.felk.cvut.cz, Ondřej Drbohlav (OD) drbohlav@cmp.felk.cvut.cz
Where and when: KN:E-301 at Building G, Karlovo namesti, Monday 16:15-17:45
Lectures are streamed live on YouTube at the time of lecture: online stream of the lecture room KN:E-301
Recorded lectures playlist
Week | Date | Lect. | Slides | Topic | Wiki | Additional material | |
---|---|---|---|---|---|---|---|
1 | 25.9. | JM | Introduction. Basic notions. The Bayesian recognition problem | Machine_learning Naive_Bayes_classifier | some simple problems | ||
2 | 2.10. | OD | Non-Bayesian tasks | Minimax | |||
3 | 9.10. | JM | Parameter estimation of probabilistic models. Maximum likelihood method | Maximum_likelihood | |||
4 | 16.10. | JM | Nearest neighbour method. Non-parametric density estimation. | K-nearest_neighbor_algorithm | |||
5 | 23.10. | JM | Logistic regression | Logistic_regression | |||
6 | 30.10. | JM | Classifier training. Linear classifier. Perceptron. | Linear_classifier Perceptron | |||
7 | 6.11. | JM | SVM classifier | Support_vector_machine | demo | ||
8 | 13.11. | JM | Adaboost learning | Adaboost | |||
9 | 20.11. | JM | no teaching | Dean's day | |||
10 | 27.11. | JM | Neural networks. Backpropagation | Artificial_neural_network | |||
11 | 4.12. | JM | Cluster analysis, k-means method | K-means_clustering K-means++ | |||
12 | 11.12. | JM | EM (Expectation Maximization) algorithm. | Expectation_maximization_algorithm | Hoffmann,Bishop, Flach | ||
13 | 18.12. | JM | Feature selection and extraction. PCA, LDA. | Principal_component_analysis Linear_discriminant_analysis | Optimalizace (CZ): PCA slides, script 7.2 | ||
14 | 8.1. | JM | Decision trees. | Decision_tree Decision_tree_learning | Rudin@MIT |
Duda R.O., Hart, P.E.,Stork, D.G.: Pattern Classification, John Willey and Sons, 2nd edition, New York, 2001
Conditions for assessment are in the lab section.