(*) 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 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.
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).
Beurteilungskriterien
(*)Independent experimenting based on given problem specifications. Written and/or oral report on the results.