Deep Reinforcement Learning Hands-On: A practical and easy-to-follow guide to RL from Q-learning and DQNs to PPO and RLHF
by Maxim Lapan
Deep Reinforcement Learning Hands-On offers a practical introduction to reinforcement learning, progressing from Q-learning and DQNs to PPO and RLHF. Maxim Lapan presents the subject in an accessible, easy-to-follow format for readers who want to understand key approaches in modern deep reinforcement learning.
About This Book
Deep Reinforcement Learning Hands-On presents a practical introduction to reinforcement learning and its deep learning applications.
The book covers foundational approaches including Q-learning and deep Q-networks, commonly known as DQNs.
It also introduces more advanced methods such as proximal policy optimization, or PPO, and reinforcement learning from human feedback, or RLHF.
Written by Maxim Lapan, the guide is intended to make these topics accessible and easy to follow.
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