Machine Learning and Pattern Classification
344.009, KV, 3 hrs., SS 2018
Univ.-Prof. Dr. Gerhard Widmer
This class will be taught in English.
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
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
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.
ContentsBasic notions and methods of machine learning, pattern classification, and statistical data modelling, including
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):