392001 Grundlagen künstlicher Kognition II (V) (SoSe 2016)
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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 | H11 | 11.04.-22.07.2016 |
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Examinations
| Date | Time | Format / Room | Comment about examination |
|---|---|---|---|
| Monday, July 18, 2016 | 12-14 | H12 | |
| Monday, September 19, 2016 | 14-16 | H1 | Nachklausur |
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Subject assignments
| Module | Course | Requirements | |
|---|---|---|---|
| 39-Inf-13 Foundations of computational cognition | Grundlagen künstlicher Kognition II | Student information | |
| - | Ungraded examination | Student information | |
| 39-Inf-13_a Grundlagen künstlicher Kognition | Grundlagen künstlicher Kognition II | Ungraded examination
|
Student information |
| 39-Inf-MIKE Modularized Individual Addition | - | Ungraded examination | 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.
| Degree programme/academic programme | Validity | Variant | Subdivision | Status | Semester | LP | |
|---|---|---|---|---|---|---|---|
| Studieren ab 50 |
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- Friday, December 11, 2015
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- Wednesday, March 23, 2016
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- Tuesday, March 22, 2016
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- lecture (V) / 2
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- Faculty of Technology
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