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Table of Contents

Lab exercises

Instructors: Petr Pošík, Jiří Spilka

  • Czech labs: Tuesdays, 14:30-16:00, room KN:E-132
  • English lab: Tuesdays, 16:15-17:45, room KN:E-132

Work in progress, update for the upcoming semester.

TypeWhenParallel IDURIDescription
tutorialTue16:15 – 17:45101LinkBBB conference room for course UI
tutorialTue14:30 – 16:00102LinkRecording of BBB conference room for course UI

Schedule

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
courses/ui/exercises/start.txt · Last modified: 2021/03/16 08:34 by spilkjir