Quick links: Schedule | Forum | Forum (2023/2024) | BRUTE task submission system | Labs
This course introduces statistical decision theory and surveys canonical and advanced classifiers such as perceptrons, AdaBoost, support vector machines, and neural nets.
Winter semester 2024/2025
Teaching: Jiří Matas (JM) matas@fel.cvut.cz, Ondřej Drbohlav (OD) drbohlav@fel.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
Week | Date | Lect. | Slides | Topic | Wiki | Additional material | |
---|---|---|---|---|---|---|---|
1 | 23.9. | OD | Introduction. Basic notions. The Bayesian recognition problem | Machine_learning Naive_Bayes_classifier | some simple problems | ||
2 | 30.9. | JM | Non-Bayesian tasks | Minimax | |||
3 | 7.10. | JM | Parameter estimation of probabilistic models. Maximum likelihood method | Maximum_likelihood | |||
4 | 14.10. | JM | Nearest neighbour method. Non-parametric density estimation. | K-nearest_neighbor_algorithm | |||
5 | 21.10. | JM | Logistic regression | Logistic_regression | |||
6 | 28.10. | no teaching | State holiday | ||||
7 | 4.11. | JM | Classifier training. Linear classifier. Perceptron. | Linear_classifier Perceptron | |||
8 | 11.11. | JM | SVM classifier | Support_vector_machine | demo | ||
9 | 18.11. | JM | Adaboost learning | Adaboost | |||
10 | 25.11. | JM | Neural networks. Backpropagation | Artificial_neural_network | |||
11 | 2.12. | JM | Cluster analysis, k-means method | K-means_clustering K-means++ | |||
12 | 9.12. | JM | EM (Expectation Maximization) algorithm. | Expectation_maximization_algorithm | Hoffmann,Bishop, Flach | ||
13 | 16.12. | JM | Feature selection and extraction. PCA, LDA. | Principal_component_analysis Linear_discriminant_analysis | Optimalizace (CZ): PCA slides, script 7.2 | ||
14 | 6.1. | 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.