392002 Übungen zu Grundlagen künstlicher Kognition II (Ü) (SoSe 2014)
Contents, comment
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Es werden verschiedene Probleme des maschinellen Lernens und der Neuroinformatik formalisiert und unterschiedliche Algorithmen eingeführt, die Beispielprobleme in konkreten Situationen algorithmisch lösen können. Themen sind etwa: Klassifikation und Regression durch Lazy learning, lineare Verfahren, Perzeptron/Adatron, Bayes-Klassifikator, zeitliche Aspekte behandelt durch MDPs, unüberwachte Verfahren wie Oja/Sanger, Fuzzy-Clustering, Grundlagen der Lerntheorie.
Teaching staff
Dates ( Calendar view )
| Frequency | Weekday | Time | Format / Place | Period |
|---|
Subject assignments
| Module | Course | Requirements | |
|---|---|---|---|
| 39-Inf-13 Grundlagen künstlicher Kognition | Grundlagen künstlicher Kognition II | Ungraded examination
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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.
- Registered number: 66
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- SS2014_392002@ekvv.uni-bielefeld.de
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- Coverage:
- 12 Students to be reached directly via email
- Notes:
- Additional notes on the electronic mailing lists
- Last update basic details/teaching staff:
- Friday, December 11, 2015
- Last update times:
- Thursday, October 22, 2015
- Last update rooms:
- Wednesday, July 16, 2014
- Type(s) / SWS (hours per week per semester)
- exercise (Ü) / 2
- Department
- Faculty of Technology
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