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deep reinforcement learning hands-on 2nd edition maksim lapan pdf
Deep Reinforcement Learning Hands-On, 2nd Edition by Maxim Lapan is a practical guide to understanding and implementing deep reinforcement learning (DRL) algorithms using Python and popular libraries like PyTorch. The book provides hands-on examples, step-by-step explanations, and insights into key DRL concepts, such as Q-learning, policy gradient methods, and Actor-Critic techniques. It is designed to help readers build their own intelligent agents and solve real-world problems, with a focus on creating and training deep neural networks that can make decisions in complex environments. The second edition includes updated content, new techniques, and examples to reflect the latest developments in the field of reinforcement learning.
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