392001 Grundlagen künstlicher Kognition II (V) (SoSe 2013)
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 | |
|---|---|---|---|---|---|
| weekly | Di | 14-16 | H11 | 08.04.-19.07.2013 |
Examinations
| Date | Time | Format / Room | Comment about examination |
|---|---|---|---|
| Tuesday, July 23, 2013 | 14-16 | H15 | |
| Tuesday, October 8, 2013 | 14-16 | H15 | Nachklausur |
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Subject assignments
| Module | Course | Requirements | |
|---|---|---|---|
| 39-Inf-13 Foundations of computational cognition Grundlagen künstlicher Kognition | Grundlagen künstlicher Kognition II | Student information | |
| - | Ungraded examination | Student information |
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- Friday, December 11, 2015
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- Wednesday, April 10, 2013
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- Wednesday, April 10, 2013
- Type(s) / SWS (hours per week per semester)
- lecture (V) / 2
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- Faculty of Technology
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