The "Applied Deep Learning" lecture is held on Mondays. Start at 8:30 am.
Zoom: https://uni-bielefeld.zoom.us/j/92186588995?pwd=UGNXdm5XRVNwMFgxdXdWV25mS2tzUT09
Meeting ID: 921 8658 8995
Passcode: 123123
We use Slack for communication: https://adl-2021wise.slack.com
Slack invitation link: https://join.slack.com/t/adl-2021wise/shared_invite/zt-x1horptw-5HZl9rSkTj4i242Y4FvJ7w
Many of the lectures will be available in video recordings (check the general Slack channel).
Tutorials will begin with the 3rd lecture.
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In this lecture, we will discuss practical approaches to deep learning that lead to the following applications:
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Deep Face Editing with StyleGAN
https://ni.www.techfak.uni-bielefeld.de/node/3682
Deep Computer Vision
https://ni.www.techfak.uni-bielefeld.de/node/3680
Physical Reasoning AI
https://ni.www.techfak.uni-bielefeld.de/node/3683
Learn to Manipulate Objects with Robotic Hands in Simulated Environments
https://ni.www.techfak.uni-bielefeld.de/node/3678
Learn to Move in Simulated Environments
https://ni.www.techfak.uni-bielefeld.de/node/3679
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Rhythmus | Tag | Uhrzeit | Format / Ort | Zeitraum |
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Modul | Veranstaltung | Leistungen | |
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39-M-Inf-VML Vertiefung Maschinelles Lernen | Vertiefung Maschinelles Lernen | Studieninformation |
Die verbindlichen Modulbeschreibungen enthalten weitere Informationen, auch zu den "Leistungen" und ihren Anforderungen. Sind mehrere "Leistungsformen" möglich, entscheiden die jeweiligen Lehrenden darüber.
Types of exams and conditions for credits.
Option 1: Oral exam with mark about the lecture topics. Successful oral exam yields 5 credits.
Option 2: The exercise tasks are done within a mini-project. Finally there is an oral exam with questions about the mini-project. Successful miniproject report and oral exam with questions about the mini-project yields 5 credits.