This course introduces statistical decision theory and surveys canonical and advanced classifiers such as perceptrons, AdaBoost, support vector machines, and neural nets.
Winter semester 2020/2021
Due to the covid-19 situation, the lectures will be given online, via zoom. All students enrolled in KOS will be sent a link at 12:30.
Where and when: KN:G-205 at Building G, Karlovo namesti, Monday 12:45-14:15
Teaching: Jiří Matas (JM) matas@cmp.felk.cvut.cz, Ondřej Drbohlav (OD) drbohlav@cmp.felk.cvut.cz
Week | Date | Lect. | Slides | Topic | Wiki | Additional material | |
---|---|---|---|---|---|---|---|
1 | 21.9. | JM | pdf recording | Introduction. Basic notions. The Bayesian recognition problem | Machine_learning Naive_Bayes_classifier | some simple problems | |
2 | 28.9. | – | (holiday, no lecture) | ||||
3 | 5.10. | JM | pdf recording | Non-Bayesian tasks | Minimax | ||
4 | 12.10. | JM | pdf recording | Parameter estimation of probabilistic models. Maximum likelihood method | Maximum_likelihood | ||
5 | 19.10. | JM | pdf recording | Nearest neighbour method. Non-parametric density estimation. | K-nearest_neighbor_algorithm | ||
6 | 26.10. | JM | pdf recording | Logistic regression | Logistic_regression | ||
7 | 2.11. | JM | pdf recording | Classifier training. Linear classifier. Perceptron. | Linear_classifier Perceptron | ||
8 | 9.11. | JM | pdf recording | SVM classifier | Support_vector_machine | ||
9 | 16.11. | JM | pdf recording | Adaboost learning | Adaboost | ||
10 | 23.11. | JM | pdf recording | Neural networks. Backpropagation | Artificial_neural_network | ||
11 | 30.11. | JM | pdfrecording | Cluster analysis, k-means method | K-means_clustering K-means++ | ||
12 | 7.12. | JM | pdfrecording | EM (Expectation Maximization) algorithm. | Expectation_maximization_algorithm | Hoffmann,Bishop, Flach | |
13 | 14.12. | JM | pdf recording | Feature selection and extraction. PCA, LDA. | Principal_component_analysis Linear_discriminant_analysis | Optimalizace (CZ): PCA slides, script 7.2 | |
14 | 4.1. | JM | pdf recording | Decision trees. | Decision_tree Decision_tree_learning | Rudin@MIT |