[ 536AIBAHO1K19 ] KV (*)Hands-on AI I
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(*) Leider ist diese Information in Deutsch nicht verfügbar. |
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Workload |
Ausbildungslevel |
Studienfachbereich |
VerantwortlicheR |
Semesterstunden |
Anbietende Uni |
3 ECTS |
B1 - Bachelor 1. Jahr |
Informatik |
Sepp Hochreiter |
2 SSt |
Johannes Kepler Universität Linz |
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Detailinformationen |
Quellcurriculum |
Bachelorstudium Artificial Intelligence 2019W |
Ziele |
(*)Hands-on AI I provides a first direct contact with modern AI approaches. The focus of this course is mainly put on Deep Learning and Reinforcement Learning techniques. Objectives are practical applications and getting an overview of newest Deep Learning approaches. All of the shown techniques will be taught in much greater detail later in the studies.
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Lehrinhalte |
(*)- Reading-in of datasets, visualize
- Using Deep Learning frameworks like Pytorch
- Playing around with the first Artificial Neural Networks
- Vanishing gradient problem, visualization and solutions
- Testing and playing around with various different Deep Learning architectures, e.g. Convolutional Neural Networks, LSTM, Autoencoders, Generative Adversarial Networks, ...
- Looking at simple Reinforcement Learning problems
- Looking at latest Reinforcement Learning problems and applying Deep Learning techniques
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Beurteilungskriterien |
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Abhaltungssprache |
Englisch |
Lehrinhalte wechselnd? |
Nein |
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Präsenzlehrveranstaltung |
Teilungsziffer |
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Zuteilungsverfahren |
Direktzuteilung |
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