Reinforcement Learning - Goal Oriented Intelligence

This series is all about reinforcement learning (RL)! Here, we'll gain an understanding of the intuition, the math, and the coding involved with RL. We'll first start out with an introduction to RL where we'll learn about Markov Decision Processes (MDPs) and Q-learning. We'll then move on to deep RL where we'll learn about deep Q-networks (DQNs) and policy gradients. We'll also build some cool RL projects in code using Python, PyTorch, and OpenAI Gym.

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