Inhalt

[ 536COSCPP2V20 ] VL (*)Programming in Python II

Versionsauswahl
(*) Leider ist diese Information in Deutsch nicht verfügbar.
Workload Ausbildungslevel Studienfachbereich VerantwortlicheR Semesterstunden Anbietende Uni
1,5 ECTS B1 - Bachelor 1. Jahr Artificial Intelligence Sepp Hochreiter 1 SSt Johannes Kepler Universität Linz
Detailinformationen
Quellcurriculum Bachelorstudium Artificial Intelligence 2024W
Ziele (*)Programming in Python II enables the students to solve more complex scientific tasks in the area of machine learning (ML) and AI by implementing a medium-sized ML project from start to finish using the popular ML framework PyTorch (having completed Programming in Python I is highly recommended). After completing the course, students will be able to realize ML projects, including the implementation of data preparation, data (pre)processing pipelines, neural network architectures, model training and model evaluation in Python and PyTorch.
Lehrinhalte (*)
  • A full-fledged machine learning project with PyTorch:
    **Collection of data
    **Analysis of the data
    **Preprocessing of the data
    **Loading of the data
    **Implementation of a Neural Network (inference)
    **Implementation of a Neural Network (training)
    **Implementation of data augmentation
    **Evaluation of performance
Beurteilungskriterien (*)Online Exams
Abhaltungssprache Englisch
Lehrinhalte wechselnd? Nein
Äquivalenzen (*)in collaboration with 536COSCPP2U20: UE Programming in Python II (1.5 ECTS) equivalent to
536COSCPP2K19: KV Programming in Python II (3 ECTS)
Präsenzlehrveranstaltung
Teilungsziffer -
Zuteilungsverfahren Direktzuteilung