Lab exercises

Instructors: Petr Pošík, Jiří Spilka

Work in progress, update for the upcoming semester.

Date	Week	Odd/Even	Contents	Link
19.02.2019	1.	E	Course organization. Intro to Python/ML	Intro
26.02.2019	2.	O	Bayesian and non-bayesian decision tasks	ML 1
05.03.2019	3.	E	Linear regression	ML 2
12.03.2019	4.	O	Non-linear models via basis expansion, logistic regression	ML 3
19.03.2019	5.	E	Model evaluation and diagnostics	ML 4
26.03.2019	6.	O	Decision trees and ensemble models	ML 5
02.04.2019	7.	E	Semestral task 1, Neural networks	ST1a, ST1b, ML 6
09.04.2019	8.	O	A brief intro to ST1, Bayesian networks	PM 1
16.04.2019	9.	E	Hidden Markov Models 1	PM 2
23.04.2019	10.	O	Hidden Markov Models 2	ST2, PM 3
30.04.2019	11.	E	Hierarchical Task Net (HTN) Planning	HTN
07.05.2019	12.	O	Constraint satisfaction problems	CSP
14.05.2019	13.	E	Schedule as on Wednesday
21.05.2019	14.	O	Scheduling	CPM