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 2015/2016 by Andreas Nürnberger, and the seminar 'Machine Learning for Medical Systems', which will took place every week. The time for the seminar will be coordinated at the first lecture date. More information will be published on this site later. This site will be regularly updated throughout the course.
The module provides an introduction to the principles, techniques, and applications of Machine Learning. Topics covered include among others:
- value functions
- concept spaces and concept learning
- instance based learning
- decision trees
- neural networks
- Bayesian learning
- reinforcement learning
- association rule learning
- genetic algorithms
Module Schedule and Room Assignments
|Lecture||Thursday 3:15 - 4:45pm||15.10.2015||G02-210|
|Seminar||Wednesday 7:15 - 8:45am||21.10.2015||G29-K058|
If you have any questions concerning the lectures or assignments please contact (if possible by email):
- Prof. Andreas Nürnberger
- Marcus Thiel
Requirements for the Oral Exam and the 'Schein'
All students are required to participate in the seminar classes. Each week, there will be an assignment sheet that will be handed out one week in advance. This sheet has to be prepared by every student and will be discussed in class. Prerequisites for an oral exam and a 'Schein' is fulfillment of the following criteria:
- Solving at least 2/3 of all questions of understanding
- Presenting at least 2 solutions in class.
The exam will be oral. For the 'Schein', there will be also an oral colloquium of about 10 minutes.
- Machine Learning
- Artificial Intelligence: A Modern Approach
S. Russel und P. Norvig
Prentice Hall, Englewood Cliffs, 2003