703722 Machine Learning

winter semester 2011/2012 | Last update: 19.03.2012 Place course on memo list
Department of Computer Science Department of Computer Science
Univ.-Prof. Justus Piater, PhD Univ.-Prof. Justus Piater, PhD, +43 512 507 53264
703722
Machine Learning
PS 1
2
weekly
annually
English
How can we design learning software systems that adjust their parameters according to example data, continually optimize their own performance, and/or automatically adapt to changing contexts? This course conveys knowledge of basic techniques and competences in the formulation and solution of problems of machine learning.
Fundamentals in statistical methods, classification and regression; plus selected topics
The lecture covers theoretical material that is exercised in discussions and written problems, as well as in programming projects.
The final grade is composed of a written exam and written exercises and programming projects.
This course will closely follow parts of Pattern Recognition and Machine Learning by Chris Bishop. Buying your personal copy is recommended.
Basic familiarity with probability theory, linear algebra, and calculus will be helpful.
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Date Time Location
Tue 2011-10-04
 13.15 - 14.00 HS 10 HS 10 Barrier-free
Tue 2011-10-11
 13.15 - 14.00 HS 10 HS 10 Barrier-free
Tue 2011-10-18
 13.15 - 14.00 HS 10 HS 10 Barrier-free
Tue 2011-10-25
 13.15 - 14.00 HS 10 HS 10 Barrier-free
Tue 2011-11-08
 13.15 - 14.00 HS 10 HS 10 Barrier-free
Tue 2011-11-15
 13.15 - 14.00 HS 10 HS 10 Barrier-free
Tue 2011-11-22
 13.15 - 14.00 HS 10 HS 10 Barrier-free
Tue 2011-11-29
 13.15 - 14.00 HS 10 HS 10 Barrier-free
Tue 2011-12-06
 13.15 - 14.00 HS 10 HS 10 Barrier-free
Tue 2011-12-13
 13.15 - 14.00 HS 10 HS 10 Barrier-free
Tue 2012-01-10
 13.15 - 14.00 HS 10 HS 10 Barrier-free
Tue 2012-01-17
 13.15 - 14.00 HS 10 HS 10 Barrier-free
Tue 2012-01-24
 13.15 - 14.00 HS 10 HS 10 Barrier-free
Tue 2012-01-31
 13.15 - 14.00 HS 10 HS 10 Barrier-free