Modern Reinforcement Learning: Deep Q Learning in PyTorch

In this complete deep reinforcement learning course you will learn a repeatable framework for reading and implementing deep reinforcement learning research ... In this complete deep reinforcement learning course you will learn a repeatable framework for reading and implementing deep reinforcement learning research papers. You will read the original papers that introduced the Deep Q learning, Double Deep Q learning, and Dueling Deep Q learning algorithms. You will then learn how to implement these in pythonic and concise PyTorch code, that can be extended to include any future deep Q learning algorithms. These algorithms will be used to solve a variety of environments from the Open AI gym's Atari library, including Pong, Breakout, and Bankheist. You will learn the key to making these Deep Q Learning algorithms work, which is how to modify the Open AI Gym's Atari library to meet the specifications of the original Deep Q Learning papers.