Machine Learning

This web page gives information on the lecture 'Machine Learning' which is held during winter term 2016/2017 by Andreas Nürnberger. It will be constantly updated during the course.

The course 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
  • clustering
  • decision trees
  • neural networks
  • Bayesian learning
  • reinforcement learning
  • association rule learning
  • genetic algorithms

Course Schedule and Room Assignments

  Time Start Room
Lecture Tuesday 3:15 - 4:45pm 11.10.2016 G22A-211 G02-109
Exercises (1st group) Monday 3:15 - 4:45pm 17.10.2016 G22A-120 (40 people)
Exercises (2nd group) Monday 1:15 - 2:45pm 17.10.2016 G22A-105 (40 people)
Exercises (3rd group) Tuesday 1:15 - 2:45pm 18.10.2016 G22A-113 (24 people)
Exam (Update!) Thursday 1:00 - 3:00pm! 09.02.2017 G29-307

Post-Exam Review

If you want to have a look at your exam, in order to know, what you have made right and wrong, please contact me at

Starting from the 13th of March until the 10th of April, I am not available. If you still want to see your exam during that period of time, please schedule an appointment with my colleague, Johannes Schwerdt, at


Registration for the individual groups is done in the exercises themselves.

Course Staff

If you have any questions concerning the lectures or assignments please contact (if possible by email):

Requirements for the Written Exam and the 'Schein'

All students are required to participate in the exercise classes. Every 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. There are two different types of assignments: questions of understanding and programming assignments. The programming assignments can be solved in small groups of up to three students and must be sent in before the respective class. Prerequisites for a written exam and a 'Schein' is fulfillment of the following criteria:

  • Gaining at least 1/2 of all programming points
  • Solving at least 2/3 of all questions of understanding
  • Presenting at least 2 solutions in class.

The exam will be written. For the 'Schein', you have to write the exam as well. The exam will be on the 9th of February 2017 in the room G29-307 (FIN-Hörsaal).

General remarks concerning the exam:

  • The main focus will be on the topics, that were also discussed in the exercises.
  • Theoretical questions (knowledge and understanding) will be from all parts of the lecture.
  • Practical tasks will be similar to the exercise assignments.


Lecture Slides
Assignment Sheets
Other Resources


Last Modification: 07.03.2017 - Contact Person: