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  • Master Seminar: Machine Learning for Student Projects in Engineering

Master Seminar: Machine Learning for Student Projects in Engineering

The seminar targets two types of participants:
* Students can present regular progress reports of an engineering project (e.g., a student or semester project or a Masters thesis) with a significant connection to machine learning. The presentations are followed by a group discussion, as well as by feedback from the lecturers.
* Students can prepare a lecture-style presentation based on the provided literature, on a topic from the field of machine learning.

Presentations are held during seminar sessions. They are followed by a group discussion. Each participant must present one topic and
participate in the discussions.

Exam: presentations and discussions during the semester

Note: limited number of participants; priority is given to project groups



Course type
Summer Term 2019


Takes place every week on Thursday from 14:00 to 16:00 in room NB 3/72.
First appointment is on 04.04.2019
Last appointment is on 11.07.2019


Some background in machine learning is recommended for presentations on topics from the literature.

The Institut für Neuroinformatik (INI) is a central research unit of the Ruhr-Universität Bochum. We aim to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory systems and while acting in those environments through effector systems. Inspired by our insights into such natural cognitive systems, we seek new solutions to problems of information processing in artificial cognitive systems. We draw from a variety of disciplines that include experimental approaches from psychology and neurophysiology as well as theoretical approaches from physics, mathematics, electrical engineering and applied computer science, in particular machine learning, artificial intelligence, and computer vision.

Universitätsstr. 150, Building NB, Room 3/32
D-44801 Bochum, Germany

Tel: (+49) 234 32-28967
Fax: (+49) 234 32-14210