Lernende Systeme/Machine Learning (WS 2009/2010)

General Information

• For a general course description please read the corresponding pages from the WIAI module guide.
• You find administrative information at UnivIS.
• Participants should sign up for the course in the virtual campus.

Recommended Reading / Links

Recommended textbook:

• Tom Mitchell: Machine Learning, McGraw Hill, 1997.

Relevant links:

• Machine Learning Eintrag bei aaai.org
• Machine Learning Abschnitt bei AI on the Web
• UCI Machine Learning Repository

Lecture Notes

1. Basic Concepts of Machine Learning [PDF]
2. Foundations of Concept Learning [PDF]
3. Decision Trees [PDF]
4. Perceptrons and Multilayer-Perceptrons [PDF]
5. Human Concept Learning [PDF]
6. Inductive Logic Programming [PDF]
7. Genetic Algorithms / Genetic Programming [PDF]
8. Instance-based Learning [PDF]
9. Kernel Methods  [PDF]
10. Bayesian Learning [PDF]
11. Computational Learning Theory [PDF]
12. Reinforcement Learning [PDF]
13. Inductive Program Synthesis [PDF]
14. Analytical Learning [PDF]
15. Further Topics in and Applications of Machine Learning

Course Archive

[WS 04/05] [SS 05] [WS 05/06] [WS 06/07] [<link kogsys/teaching/archiv/ws0708/lernende_systeme/ - extern>WS 07/08</link>] [<link kogsys/teaching/archiv/ws0809/lernende_systeme/ - extern>WS 08/09</link>]