[ 921CGELPRMU13 ] UE (*)Probabilistic Models
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| (*) Leider ist diese Information in Deutsch nicht verfügbar. |
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| Workload |
Ausbildungslevel |
Studienfachbereich |
VerantwortlicheR |
Semesterstunden |
Anbietende Uni |
| 1,5 ECTS |
M1 - Master 1. Jahr |
Informatik |
Gerhard Widmer |
1 SSt |
Johannes Kepler Universität Linz |
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| Detailinformationen |
| Quellcurriculum |
Masterstudium Computer Science 2022W |
| Ziele |
(*)To provide an opportunity for students to experiment with probabilistic models and reasoning methods, in order to better understand the workings and limitations of these methods. This class is highly recommended as a supplementary course to the VO "Probabilistic Models", where the theoretical foundations are explained.
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| Lehrinhalte |
(*)Practical experiments with probabilistic models. Development of simple systems that model and reason about some given problem. Specific focus: (discrete) Bayes Nets and temporal models (Hidden Markov Models, Kalman Filter).
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| Beurteilungskriterien |
(*)Independent experimenting based on given problem specifications. Written and/or oral report on the results.
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| Abhaltungssprache |
Englisch |
| Lehrinhalte wechselnd? |
Nein |
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| Präsenzlehrveranstaltung |
| Teilungsziffer |
35 |
| Zuteilungsverfahren |
Direktzuteilung |
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