392001 Grundlagen künstlicher Kognition II (V) (SoSe 2015)
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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: einfache Modellierung biologischer Neuronen, lineare Klassifikation: das Perzeptron, MaxMinOver, das Adatron, nichtlineare Klassifikation: Kerne, RBF, ELM, Mehrschichtnetze, lineare und nichtlineare Regression, unüberwachtes Lernen durch Oja, Grundlagen der Lerntheorie
Teaching staff
Dates ( Calendar view )
| Frequency | Weekday | Time | Format / Place | Period | |
|---|---|---|---|---|---|
| weekly | Di | 14-16 | T2-205 | 07.04.-17.07.2015 |
Examinations
| Date | Time | Format / Room | Comment about examination |
|---|---|---|---|
| Thursday, July 9, 2015 | 14-16 | H1 | |
| Monday, September 14, 2015 | 14-16 | H1 | 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 | |
| 39-Inf-MIKE Modularized Individual Addition Modularisierter individueller Kompetenz-Erwerb (MiKE) | - | Ungraded examination | Student information |
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- Last update basic details/teaching staff:
- Friday, December 11, 2015
- Last update times:
- Thursday, October 22, 2015
- Last update rooms:
- Friday, May 22, 2015
- Type(s) / SWS (hours per week per semester)
- lecture (V) / 2
- Department
- Faculty of Technology
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