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Deep Reinforcement Learning in Action by Alexander Zai and Brandon Brown (2020,

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Deep Reinforcement Learning in Action: A Comprehensive Guide to Building Intelligent AI Agents

In their new book, “Deep Reinforcement Learning in Action,” authors Alexander Zai and Brandon Brown provide a detailed and practical guide to implementing deep reinforcement learning algorithms in real-world applications. This comprehensive guide covers everything from the basics of deep learning and reinforcement learning to advanced techniques for training intelligent AI agents.

Whether you’re a seasoned machine learning practitioner or a newcomer to the field, this book has something to offer. With hands-on examples and code snippets in Python, Zai and Brown walk you through the process of building and training deep reinforcement learning models from scratch. You’ll learn how to use popular libraries like TensorFlow and Keras to implement state-of-the-art algorithms such as deep Q-learning, policy gradients, and actor-critic methods.

Through a series of practical exercises and projects, you’ll gain a deep understanding of how deep reinforcement learning works and how to apply it to solve complex problems in domains like robotics, gaming, and finance. By the end of the book, you’ll have the knowledge and skills to build your own intelligent AI agents that can learn and adapt to their environments in real-time.

“Deep Reinforcement Learning in Action” is a must-read for anyone interested in the cutting-edge field of deep reinforcement learning. Whether you’re a researcher, a developer, or just a curious enthusiast, this book will help you unlock the full potential of AI and create intelligent systems that can truly learn from their experiences.
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