Lab exercises

Instructors: Petr Pošík, Jiří Spilka

Work in progress, update for the upcoming semester.

Links to BBB rooms/recordings

The column Deadlines is just for an overall picture. The actual deadlines are always in BRUTE.

Date	W#	Contents	Link	Deadlines	Note
16.02.	1	Course organization. Intro to Python/ML	Intro	-
23.02.	2	Bayesian and non-bayesian decision tasks	ML 1	-
02.03.	3	Linear regression	ML 2	Last week for ML 2
09.03.	4	Sem. task 1a and 1b. Logistic regression, basis expansion.	ML 3	Last week for ML 3
16.03.	5	Model evaluation and diagnostics	ML 4	Last week for ML 4	Updated Task 1b, cf. comments
23.03.	6	Decision trees and ensemble models	ML 5	Last week for ML 5
30.03.	7	Neural networks	ML 6	Last week for ML 6
06.04.	8	Semestral task 2. Bayesian networks	PM 1	Last week for ST1	ST1 report checklist
13.04.	9	Hidden Markov Models 1	PM 2	-
20.04.	10	Hidden Markov Models 2	PM 3	Last week for PM 2+3
27.04.	11	Hierarchical Task Net (HTN) Planning	HTN	Last week for HTN.
04.05.	12	Constraint satisfaction problems	CSP	Last week for ST2
11.05.	13	Scheduling	CPM	Last week for CSP
18.05.	14	Reserve, questions, consultations.		Last week for CPM