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[N] UC Berkeley’s CS 285: Deep Reinforcement Learning

http://rail.eecs.berkeley.edu/deeprlcourse/

Lectures are recorded and live streamed

Material which will be covered:

  1. From supervised learning to decision making

  2. Model-free algorithms: Q-learning, policy gradients, actor-critic

  3. Advanced model learning and prediction

  4. Transfer and multi-task learning, meta-learning

  5. Exploration

  6. Open problems, research talks, invited lectures

There’s a subreddit for this course: r/berkeleydeeprlcourse

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