2020W
Silvan David Peter
Institut für Kunst und Gesellschaft, Cross-Disciplinary Strategies
2021S, Vorlesung und Übungen (VU), 2.0 ECTS, 1.0 SemStd., LV-Nr. S30453
We will have an in-depth look at the basic ideas and problems in Machine Learning (ML) and AI by training neural networks in the web application Teachable Machine. How do we collect and prepare training data? How do we check whether the algorithm is actually learning what it is supposed to learn? What types of bias could degrade the performance of an ML algorithm, and what could be the consequences if algorithms are deployed in the real world?
Moreover, we will integrate ML algorithms with a simple interactive application in the development environment p5.js. Here, the focus will be on producing sound/musical output in response to visual cues that the algorithm will detect from a webcam video stream. We will therefore also look into the basics of sound synthesis within p5.js/JavaScript. Your creativity is welcome in this task!
This course will be held in close collaboration with „Digital Skills“. It is strongly recommended to attend both courses.
This is the second part of a two-part course, be aware that familiarity with p5js is expected. It is recommended to attend “Digital Skills” in parallel to this lecture.
Code, Software Programming, Interaction, Audio
05. März 2021, 12:00–12:45 Zoom
12. März 2021, 12:00–12:45 Zoom
19. März 2021, 12:00–12:45 Zoom
26. März 2021, 12:00–12:45 Zoom
16. April 2021, 12:00–12:45 Zoom
23. April 2021, 12:00–12:45 Zoom
30. April 2021, 12:00–12:45 Zoom
07. Mai 2021, 12:00–12:45 Zoom
21. Mai 2021, 12:00–12:45 Zoom
28. Mai 2021, 12:00–12:45 Zoom
04. Juni 2021, 12:00–12:45 Zoom
11. Juni 2021, 12:00–12:45 Zoom
18. Juni 2021, 12:00–12:45 Zoom
25. Juni 2021, 12:00–12:45 Zoom
Von 01. Februar 2021, 07:00 bis 31. März 2021, 23:59
Per Online Anmeldung
Mitbelegung: möglich
Besuch einzelner Lehrveranstaltungen: möglich