Hands-On Reinforcement Learning with Python

Hands-On Reinforcement Learning with Python is your entry point into the world of artificial intelligence using the power of Python. It is an example-rich guide to master various RL and DRL algorithms. (Limited-time offer)

Book Description

Topics included: Introduction to Reinforcement Learning • Getting Started with OpenAI and TensorFlow • The Markov Decision Process and Dynamic Programming • Gaming with Monte Carlo Methods • Temporal Difference Learning • Multi-Armed Bandit Problem • Deep Learning Fundamentals • Atari Games with Deep Q Network • Playing Doom with a Deep Recurrent Q Network • The Asynchronous Advantage • Actor Critic Network • Policy Gradients and Optimization • Capstone Project – Car Racing Using DQN • Recent Advancements and Next Steps

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