Learning About Deep Reinforcement Learning (Slides)
Earlier this month, I gave an introductory talk at Data Philly on deep reinforcement learning. The talk followed the Nature paper on teaching neural networks to play Atari games by Google DeepMind and was intended as a crash course on deep reinforcement learning for the uninitiated. Get the slides below!
Deep Reinforcement Learning sounds intractable for a layperson. “Reinforcement learning” alone sounds scary (I’m reinforcing WHAT again? Random actions? Bah!), and then you add the word “deep” and most people simply drop off. This talk details what I’ve learned from replicating the original NIPS/Nature papers on Deep Reinforcement Learning for playing Atari games and walks through some python implementations of the basic steps for reinforcement learning code. The talk uses Keras (TensorFlow backend) and tries (albeit, unsuccessfully) to hide advanced mathematical formulations of the problem. By the end of the talk, we will all have taken a modest step forward in learning deep reinforcement learning.
You can access the slides here.