Institute of Computer Science
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  2. 2018/19 spring
  3. Special Course in Machine Learning: Deep Reinforcement Learning (MTAT.03.317)
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Special Course in Machine Learning: Deep Reinforcement Learning 2018/19 spring

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Projects

The idea of projects is to get hands-on experience in applying deep reinforcement learning. You can either propose your own project or choose one from here. Project team size can be 1-2 people. We expect more from 2-people project.

The result of a project is

  • the code (preferably on GitHub),
  • either blog post on Medium or paper on Arxiv,
  • presentation on the final day.

Project Milestones

By these dates you should be able to answer following questions:

  • 5.03.2019 - What is the task/environment? What is observation space? What is action space? What is reward?
  • 26.03.2019 - What algorithm you are going to use? Do you use existing codebase or implement it from scratch? What infrastructure you plan to use for training?
  • 23.04.2019 - We expect some initial results. What improvements you plan over the initial results?
  • 28.05.2019 - Final project presentations.
  • Institute of Computer Science
  • Faculty of Science and Technology
  • University of Tartu
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