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StarAi Deep Reinforcement Learning Course
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Overview
Week 1
  • Lecture 0: Introduction to Reinforcement Learning
  • Lecture 1: Epsilon-Greedy & the multiarmed bandit problem
Week 2
  • Lecture 2: Markov Decision Processes, Dynamic Programming
Week 3
  • Lecture 3: Tabular Q Gridworld
  • Lecture 4: Tabular Q Cartpole
Week 4
  • Lecture 5: NQL Theory
  • Lecture 6: DQN
Week 5
  • Lecture 7: Policy Gradient Methods
Week 6
  • Lecture 8: PySC2
`Bonus Material
  • Rainbow
  • The A2C algorithm
  • `Additional Learning Material

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Bonus: Additional Learning Material

   

Additional Learning Material

   

Further Learnings - Foundations:

Intro to Reinforcement Learning by David Silver (Deepmind)

Reinforcement Learning: An Introduction (textbook)

Denny Britz Github Repo

OpenAi Spinning Up in Deep RL

   

Further Learnings - Advanced:

Berkeley Deep RL Bootcamp

CS294 Deep Reinforcement Learning (Berkeley)

Deepmind’s IMPALA RL Framework

   

Last updated on Apr 4, 2019

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