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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Frequency | Weekday | Time | Format / Place | Period |
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Module | Course | Requirements | |
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39-M-Inf-VML Vertiefung Maschinelles Lernen | Vertiefung Maschinelles Lernen | Student information |
The binding module descriptions contain further information, including specifications on the "types of assignments" students need to complete. In cases where a module description mentions more than one kind of assignment, the respective member of the teaching staff will decide which task(s) they assign the students.
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.