Department of Computational Perception
Department of
Computational Perception
Johannes Kepler Universität Linz

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344.001, KV, 2std., WS 2005/06

Univ.-Prof. Dr. Gerhard Widmer

Institut für Computational Perception

Johannes Kepler Universität Linz

TIME: Tuesday, 12:00 - 13:30

START: Tuesday, 11.10.2005

PLACE: HS 13 (TNF Tower, Ground Floor)

NOTE: This class will be taught in English!


Machine Learning is a sub-field of Artificial Intelligence that deals with the development of computer programs that can learn in some sense. Learning is a very broad and multi-faceted concept that comprises all kinds of processes that derive general knowledge from observations and experiences. Machine Learning is an extremely active field of basic research, but many learning algorithms are also playing an increasingly important role in practical applications of intelligent systems - e.g., learning robots, adaptive user interfaces, automatic recognition and classification systems, etc. Another related and very important field of application of learning algorithms is Data Mining - the discovery of hidden and useful patterns and relationships in huge amounts of data.

The class gives an introductory overview of the basic concepts and most important methods of Machine Learning. After one semester, the students should have a basic understanding of the properties and limitations of machine learning algorithms, and should be able to critically judge and evaluate new research results in this field.


The following topics will be covered in class:

Course Materials:

pdf versions of the powerpoint slides used in class will be made available via the Web (KUSSS).

Recommended book (but not needed to pass):
Mitchell, T.M. (1997). Machine Learning. New York, N.Y.: McGraw-Hill.

Questions, Suggestions, Complaints, etc. to:

Gerhard Widmer
Tel. 2468-1510
gerhard dot widmer at jku dot at

last edited by gw on 2005-09-01