Deep Reinforcement Learning Hands-On

Deep Reinforcement Learning Hands-On, Third Edition, is a comprehensive guide that takes readers from the basics of reinforcement learning to advanced concepts.

It covers key topics such as deep Q-networks, policy gradients, and continuous control problems, using practical examples in environments like OpenAI Gym and PyTorch.

The book is ideal for machine learning engineers and data scientists looking to apply deep reinforcement learning in various industries.