Department of Computational Perception
Department of
Computational Perception
Johannes Kepler Universitšt Linz


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Machine Learning and Pattern Classification


344.009, KV, 3 hrs., SS 2018

Univ.-Prof. Dr. Gerhard Widmer

This class will be taught in English.

TIME: Monday, 12:00 - 13:30 (sometimes a bit longer)
START: Monday, March 5, 2018
PLACE: HS 17 (first time (March 5) only); then: S2 048


Goals of this class

The lecture gives an overview of standard methods in the field of pattern recognition, pattern classification, machine learning, and statistical data modelling. It covers some of the most basic concepts and methods in the field, and demonstrates the application of these methods in a variety of complex tasks, mainly from the area of audio perception and music information retrieval (which are the institute's special research focus).
The lecture is accompanied by a practical track where the students carry out a pattern classification project of real-world complexity, on real-world data, in several stages, from feature definition and extraction to the training of various classifiers and systematic experimentation.
After attending the class, the students should have a basic understanding of the central issues in pattern classification, should be able to read the scientific literature on learning and pattern classification, and should have acquired the basic skills needed to realise and evaluate pattern classification systems.

Contents

Basic notions and methods of machine learning, pattern classification, and statistical data modelling, including

Course Material

PDF versions of the powerpoint slides used in the lecture will be made available electronically, via KUSSS.

Interested students may also want to consult the following books (but this is in no way required for the class):



last edited by gw on Feb 12, 2018