Inhalt

[ 921CGELPRMU13 ] UE (*)Probabilistic Models

Versionsauswahl
(*) Leider ist diese Information in Deutsch nicht verfügbar.
Workload Ausbildungslevel Studienfachbereich VerantwortlicheR Semesterstunden Anbietende Uni
1,5 ECTS M1 - Master 1. Jahr Informatik Gerhard Widmer 1 SSt Johannes Kepler Universität Linz
Detailinformationen
Quellcurriculum Masterstudium Computer Science 2025W
Lernergebnisse
Kompetenzen
(*)See lecture series (Vorlesung) by the same name.
Fertigkeiten Kenntnisse
(*)See lecture series (Vorlesung) by the same name. (*)See lecture series (Vorlesung) by the same name.
Beurteilungskriterien (*)Implementation of, and experimentation with, simple algorithms, based on given problem specifications; written and/or oral report on the results.
Lehrmethoden (*)Students implement simple inference and learning algorithms related to probabilistic graphical models; they perform systematic experiments with toy problems and datasets, in order to deepen their understanding of probabilistic modeling and reasoning. Selected students report on their results and experiences in class.
Abhaltungssprache Englisch
Literatur (*)The lecture slides of the corresponding lecture series course (VO).
Lehrinhalte wechselnd? Nein
Sonstige Informationen (*)This exercise course (UE) and the corresponding lecture series course (VO) form a didactic unit. The study results described here are achieved through the combination of these two courses.
Präsenzlehrveranstaltung
Teilungsziffer 35
Zuteilungsverfahren Direktzuteilung