Veranstaltung: Machine Learning: Unsupervised Methods

Nummer:
310003
Lehrform:
Vorlesung und Übungen
Verantwortlicher:
Prof. Dr. Laurenz Wiskott
Dozent:
Prof. Dr. Laurenz Wiskott (Neuroinformatik)
Sprache:
Englisch
SWS:
4
LP:
6
Angeboten im:
Wintersemester

Termine im Wintersemester

  • Beginn: Dienstag den 09.10.2018
  • Vorlesung m. int. Übung Dienstags: ab 12:15 bis 13.45 Uhr im NB 3/57

Prüfung

Termin nach Absprache mit dem Dozenten.

Prüfungsform:mündlich
Prüfungsanmeldung:FlexNow
Dauer:30min

Ziele

After visiting this course students have knowledge in several methods of machine learning, i.e.: principal component analysis, clustering, vector quantization, self-organizing maps, independent component analysis, Bayesian theory and graphical models, linear regression, backpropagation of error, generalization and support vector machines.

Inhalt

This course covers a variety of methods from machine learning such as principal component analysis, clustering, vector quantization, self-organizing maps, independent component analysis, Bayesian theory and graphical models, linear regression, backpropagation of error, generalization and support vector machines.

Voraussetzungen

none

Empfohlene Vorkenntnisse

Good command of linear algebra and calculus.