Inhalt

[ 993MLPEDN1U19 ] UE (*)Deep Learning and Neural Nets I

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(*) Leider ist diese Information in Deutsch nicht verfügbar.
Workload Ausbildungslevel Studienfachbereich VerantwortlicheR Semesterstunden Anbietende Uni
1,5 ECTS M1 - Master 1. Jahr Artificial Intelligence Günter Klambauer 1 SSt Johannes Kepler Universität Linz
Detailinformationen
Quellcurriculum Masterstudium Artificial Intelligence 2024W
Ziele (*)This course will show practical applications and implementations of the contents of the “Deep Learning and Neural Nets I (3 VL)” class. Students will exercise the theory presented in the accompanying lecture and solve programming assignments. Programming assignments will be done in Python using the PyTorch framework.
Lehrinhalte (*)This course teaches how to implement

  • a deep learning framework with automatic differentiation
  • fully-connected and convolutional layers
  • optimisation algorithms and components for accelerating learning in Python and how to build full networks to solve practical tasks.
Beurteilungskriterien (*)bi-weekly assignments, exam at the end of the semester
Lehrmethoden (*)Slide presentations, presentations on blackboard, discussions, and code examples
Abhaltungssprache Englisch
Lehrinhalte wechselnd? Nein
Präsenzlehrveranstaltung
Teilungsziffer 35
Zuteilungsverfahren Direktzuteilung