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PEM_RL in other semesters:
SS23 WS2122 WS2021
Home > Teaching > SS 2023 > PEM_RL

Practical Course Development of Media Systems: Reinforcement Learning

Lecturers: Yannick Weiss, Jesse Grootjen, Florian Bemmann Professor in Charge: Prof. Sven Mayer
Hours per week: 4
ECTS-Credits: 6
Modul: Master P5.0.2 oder P5.0.4: Gruppenpraktikum zu fortgeschrittenen Themen der Informatik I oder Informatik II
After consultation with the examination board, credit for P2, P3 or P6 (advanced topics for Master) also possible

  • News
  • Contents
  • Other lectures on the topic
  • Schedule
  • Location
  • Application


News

  • 08.02.2023: This page is still under development, all content may be subject to change.


Contents

We work on solutions for the use of Machine Learning for Media Systems. During the first half we will learn some basics and consolidate it in small exercises using Python and Unity. In the second hald, you should implement your own ideas and present it as a prototype. The ideas will be implemented and presented as a prototype.



Other lectures on the topic

  • Human Computer Interaction
  • Machine Learning, e.g. Pratical Machine Learning, Intelligent User Interfaces


Schedule

Please note that due to the engaging nature of the group projects, students have to spend more than the allocated time on the development of their prototypes. This is especially true for the group project implementation scheduled during the lecture break.

Date Time Topic
09.05.2023 16:00-18:00 Lecture 1: Introduction & Project Brainstorming
23.05.2023 16:00-18:00 Lecture 2: 90-sec Paper Presentation
06.06.2023 16:00-18:00 Lecture 3: TBA
20.06.2023 16:00-18:00 Lecture 4: Project Ideation & Group Formation
04.07.2023 16:00-18:00 Lecture 5: TBA
18.07.2023 16:00-18:00 Lecture 6: TBA
28.08.2023 09:00-17:00 Work on the projects
29.08.2023 09:00-17:00 Work on the projects
30.08.2023 09:00-17:00 Work on the projects
31.08.2023 09:00-17:00 Work on the projects
01.09.2023 09:00-12:00 Work on the projects
01.09.2023 12:00-17:00 Final presentations


Location

The course takes at Location: Frauenlobstr. 7a, Room 357



Application

Interested students can apply for this practical course via Uni2Work .

The applications should include the following information:

  • Describe relevant expertise, for example from previous courses, jobs and other projects, if any, that demonstrate your skills.
  • If you already have a project idea that you would like to implement in this course, please sketch it out briefly.
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Impressum – Privacy policy – Contact  |  Last modified on 2023-03-15 by Sven Mayer (rev 41839)