Es ist eine neuere Version 2024W dieser LV im Curriculum Masterstudium Computational Mathematics 2024W vorhanden.
(*) 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 2019W
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
(*)
Automatic differentiation
Common deep learning frameworks in python
Implementing feedforward neural networks
Solving problems using deep learning techniques
Applying convolutional neural networks
Transfer learning
Beurteilungskriterien
(*)bi-weekly assignments, exam at the end of the semester
Lehrmethoden
(*)Slide presentations, presentations on blackboard, discussions, and code examples
