Inhalt

[ 921PECOMLPU20 ] UE (*)Machine Learning and Pattern Classification

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 by the same name.
Fertigkeiten Kenntnisse
(*)See lecture series by the same name. (*)See lecture series by the same name.
Beurteilungskriterien (*)Creativity and rigour in solving a complex machine learning project; clarity and systematicity of written project reports throughout the course of the project.
Lehrmethoden (*)Independent work on a complex machine learning problem by students / student groups, in several stages throughout the semester. Using public machine learning toolboxes, students go through all the stages of a pattern classification project of real-world complexity, from annotation, feature definition and extraction to the training of various classifiers and systematic experimentation. Joint discussion of ideas, experiments, and results. Presentations by lecturer and selected students or student groups.
Abhaltungssprache Englisch
Literatur (*)Lecture slides from the corresponding lecture course (VO). Additional information resources are provided if/when needed.
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.
Äquivalenzen (*)in collaboration with 921PECOMLPV20: VL Machine Learning and Pattern Classification (3 ECTS) equivalent to
921PECOMLPK13: KV Machine Learning and Pattern Classification (4.5 ECTS)
Präsenzlehrveranstaltung
Teilungsziffer 35
Zuteilungsverfahren Direktzuteilung