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- Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more
541,- This book is a practical, developer-oriented introduction to deep reinforcement learning (RL). Explore the theoretical concepts of RL, before discovering how deep learning (DL) methods and tools are making it possible to solve more complex and challenging problems than ever before. Apply deep RL methods to training your agent to beat arcade ...
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- 541,-
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- Apply modern RL methods to practical problems of chatbots, robotics, discrete optimization, web automation, and more, 2nd Edition
946,- With six new chapters, Deep Reinforcement Learning Hands-On Second edition is completely updated and expanded with the very latest reinforcement learning (RL) tools and techniques, providing you with an introduction to RL, as well as the hands-on ability to code intelligent learning agents to perform a range of practical tasks.
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- 946,-