Technische Universität München Robotics and Embedded Systems

Machine Learning

Lecturer Prof. Dr. van der Smagt
Module Modul IN2064
Type Lecture
Language English
Semester WS 2010/2011
ECTS 6.0
Audience Obligatory course for students of RCI
Elective course for students of Informatics (Diplom 5+, Bachelor 5+, Master 1+)
Elective course for students of Business Informatics (Bachelor 5+)
Prerequisite Analysis I/II, Linear Algebra I/II and Probability Theory.
Time & Location Lecture is cancelled
Certificate Final written exam


2010/10/18: Lecture is cancelled for the winter term (WS) 2010/2011


This lecture will take you on a journey through the exciting and highly active field of Machine Learning, which has applications in areas as diverse as web searches, robotics, data mining, environmental sciences, medical data analysis, and many more. The lecture will follow loosely the textbook by Christopher Bishop, referenced below.



Suggested Reading

[1] David J. C. MacKay. Information theory, inference, and learning algorithms. Cambridge Univ. Press, 2008.
[2] Christopher M. Bishop. Pattern Recognition and Machine Learning. Springer, Berlin, New York, 2006.
[3] R.S. Sutton and A.G. Barto. Reinforcement Learning: An Introduction. MIT Press, 1998.
[4] Tom M. Mitchell. Machine learning. McGraw-Hill, Boston, Mass., 1997.