Machine Learning for Medical Systems
This web page provides information on the module 'Machine Learning for Medical Systems'. The module consists of the lecture 'Machine Learning', which is given during winter term 2022/2023 by Andreas Nürnberger, and the seminar 'Machine Learning for Medical Systems', which will take place every week. The time for the seminar will be coordinated at the first lecture date. For additional information on the course and the exercise (with regular updates), please visit the Machine Learning website.
The module provides an introduction to the principles, techniques, and applications of Machine Learning. Topics covered include among others (subject to change):
- value functions
- concept spaces and concept learning
- instance based learning
- clustering
- decision trees
- neural networks
- Bayesian learning
- reinforcement learning
- association rule learning
- genetic algorithms
Module Schedule and Room Assignments
| Time | Start | Room | |
| Lecture | tba | tba | tba |
| Seminar | tba | tba | tba |
There is NO extra seminar date! Please visit the regular exercise!
Registration
Registration for the exercise is done separately in each exercise group. Please visit the Machine Learning page for more information.
Module Staff
If you have any questions concerning the lectures or assignments please contact (if possible by email):
- Prof. Andreas Nürnberger
E-Mail: andreas.nuernberger@ovgu.de - Marcus Thiel
E-Mail: marcus.thiel@ovgu.de
Requirements for the Exam and the 'Schein'
See the Course Information on Moodle for updated information.
Materials
Lecture Slides
- ...
Assignment Sheets
- Paper Template
- For seminar topics and guidance please contact:
Johannes Schwerdt
E-Mail: johannes.schwerdt@ovgu.de
Literature
- Machine Learning
Tom Mitchell
McGraw-Hill, 1997. - Artificial Intelligence: A Modern Approach
S. Russel und P. Norvig
Prentice Hall, Englewood Cliffs, 2003