Lernende Systeme/Machine Learning (WS 2018/2019)

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.
  • This course can is elegible by students of the master in Surevy Statistics (MiSS). The module is an official import module for this degree.

Recommended Reading / Links

Recommended textbook:

Relevant links/sources:

Lecture Notes

  1. Basic Concepts of Machine Learning [pdf]
  2. Foundations of Concept Learning [pdf]
  3. Decision Trees, Avoiding Overfitting [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. Bayesian Learning/Graphical Models [pdf]
  10. Kernel Methods, Support Vector Machines [pdf]
  11. Hidden Markov Models [pdf]
  12. Reinforcement Learning [pdf]
  13. Inductive Programming [pdf]
  14. Unsupervised Learning (Clusteranalysis) [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>] [WS 09/10]  [WS 10/11]  [WS 11/12]  [ WS 12/13]  [WS 13/14] [WS 14/15] [WS 15/16] [WS16/17] [WS17/18]