Otto-von-Guericke-Universität Magdeburg

 
 
 
 
 
 
 
 

Advanced Topics in Machine Learning

This web page provides information on the course Advanced Topics in Machine Learning (summer term 2017). The course deals with selected topics of Machine Learning, including:

Prerequisite for attending this course is a basic knowledge of computer science, especially in Machine Learning. Programming skills are an advantage concerning the practical exercises.

Title Time Start Room
Lecture Thursday 3:00pm - 5:00pm 06.04.2017 G22A-020
Exercises Monday 09:00am - 11:00am 10.04.2017 G22A-110

Further information on the lecture and the exercise can be found in the LSF portal.

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

The exercise classes have two objectives. First, regular assignments concerning the theory taught in the lecture will be given (about one week in advance). These have to be prepared by the students and are then discussed during class. Secondly, the lecture will be accompanied by a software project. Its goal is to practice the implementation of machine learning techniques into a larger system. This will be done as a joint group work. The development will partly be done during the exercise classes. However, further development outside the class might be necessary to complete the project. We expect active involvement of all students, both in the project and the theoretical assignments.

At the end of the course, there will be an oral exam. As a prerequisite, we expect active involvement both during the exercise and in the software project.

We will provide lecture slides, assignment sheets, and further material during the course.

Lecture Slides
Exercise Material
Further Material
Last Modification: 21.07.2017 - Contact Person: Prof. Dr.-Ing. Andreas Nürnberger