This course introduces statistical decision theory and surveys canonical and advanced classifiers such as perceptrons, AdaBoost, support vector machines, and neural nets.
Winter semester 2022/2023
Where and when: KN:E-301 at Building G, Karlovo namesti, Monday 16:15-17:45
Lectures will be streamed on YouTube, follow this link + select KN:E-301@CVUTFEL-live. Recorded lectures will be available on a YouTube playlist before Tuesday morning. For online feedback, connect via zoom link: https://feectu.zoom.us/j/6135640703
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 | 19.9. | JM | Introduction. Basic notions. The Bayesian recognition problem | Machine_learning Naive_Bayes_classifier | some simple problems | ||
2 | 26.9. | OD | Non-Bayesian tasks | Minimax | |||
3 | 3.10. | OD | Parameter estimation of probabilistic models. Maximum likelihood method | Maximum_likelihood | |||
4 | 10.10. | OD | Nearest neighbour method. Non-parametric density estimation. | K-nearest_neighbor_algorithm | |||
5 | 17.10. | OD | Logistic regression | Logistic_regression | |||
6 | 24.10. | OD | Classifier training. Linear classifier. Perceptron. | Linear_classifier Perceptron | |||
7 | 31.10. | JM | SVM classifier | Support_vector_machine | demo | ||
8 | 7.11. | JM | Adaboost learning | Adaboost | |||
9 | 14.11. | JM | Neural networks. Backpropagation | Artificial_neural_network | |||
10 | 21.11. | JM | Cluster analysis, k-means method | K-means_clustering K-means++ | |||
11 | 28.11. | JM | EM (Expectation Maximization) algorithm. | Expectation_maximization_algorithm | Hoffmann,Bishop, Flach | ||
12 | 5.12. | JM | Feature selection and extraction. PCA, LDA. | Principal_component_analysis Linear_discriminant_analysis | Optimalizace (CZ): PCA slides, script 7.2 | ||
13 | 12.12. | JM | Decision trees. | Decision_tree Decision_tree_learning | Rudin@MIT | ||
14 | 9.1. | JM | Basic notions recapitulation, links between methods, answers to exam questions | The lecture will not take place at the standard time, I'll be answering question by email or zoom link |
Conditions for assessment are in the lab section.