The subject introduces pattern recognition (called also machine learning). If there is one non-Czech speaking student in the audience, the lecture wil be in English. The subject is intended for doctoral student. I can take master students after an initial interview about student's motivation as well. The lectures are open to bachelor students but no credit for the subject will be awarded.
It is expected that student did not study this subject before, e.g. in the bachelor subject Rozpoznávání a strojové učení, B4M33RPZ, B4M33RPZ lectured by Prof. Jiří Matas. The lecturer will ask the student if she/he did not pass a similar subject to avoid getting credits easily.
The subject comprises of lectures and consultations with the lecturer (if the student asks for it).
It is required that the student passed an introductory course of the probability theory and statistics or studied this area individually.
Week | Date | Time | Content | |
---|---|---|---|---|
01 | 19.02.2019 | 16:00 | VH | Rehearsal of the basic knowledge from probability theory and statistics. Outline of pattern recognition. |
02 | 26.02.2019 | 15:15 | VH | Bayesian task and its two special cases. Non-Bayesian tasks, formulations only. Conditional independence of features. Gaussian models. |
03 | 05.03.2019 | 15:15 | RŠ | Artificial neural networks. slides |
04 | 12.03.2019 | 15:15 | VH | Data normalization. Experimental evaluation of classifiers. Receiver operator curve (ROC). |
19.03 | No lecture. | Both VH and RŠ travel this week. | ||
05 | 26.03.2019 | 15:15 | VH | Estimation of probabilistic models. Parametric and nonparametric methods. |
06 | 02.04.2019 | 15:15 | RŠ | Convolutional neural networks. slides |
07 | 04.04.2019 | 10:00 | VH | Learning in pattern recognition. (Replacement lecture) |
08 | 09.04.2019 | 15:15 | VH | Linear classifiers. Perceptron. Learning (training) algorithm. |
09 | 16.04.2019 | 15:15 | VH | VC dimension and its use. Support vector machines classifiers (SVM). Kernel methods. Training algorithms for SVM. |
10 | no lecture | 15:15 | VH | |
11 | 30.04.2019 | 15:15 | VH | Unsupervised learning. Cluster analysis. K-means algorithm. |
12 | 07.05.2019 | 15:15 | VH | Unsupervised learning. EM algorithm. |
14.05.2019 | 15:15 | RŠ | Radoslav Skoviera forgot about the lecture by mistake. We apologize deeply. | |
13 | 21.05.2019 | 15:15 | VH | Markovian models in pattern recognition. |
14 | 28.05.2019 | 15:15 | RŠ | Reinforcement learning. slides |
Registered students:
Students which have to register:
Extraordinary students
Megumi Miyashita (a visiting student from TUAT Tokyo, only till the end of February 2019)