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Books > Computing & IT > General theory of computing > Data structures
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Grokking Deep Reinforcement Learning (Paperback)
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Grokking Deep Reinforcement Learning (Paperback)
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Written for developers with some understanding of deep learning
algorithms. Experience with reinforcement learning is not required.
Grokking Deep Reinforcement Learning introduces this powerful
machine learning approach, using examples, illustrations,
exercises, and crystal-clear teaching. You'll love the perfectly
paced teaching and the clever, engaging writing style as you dig
into this awesome exploration of reinforcement learning
fundamentals, effective deep learning techniques, and practical
applications in this emerging field. We all learn through trial and
error. We avoid the things that cause us to experience pain and
failure. We embrace and build on the things that give us reward and
success. This common pattern is the foundation of deep
reinforcement learning: building machine learning systems that
explore and learn based on the responses of the environment. *
Foundational reinforcement learning concepts and methods * The most
popular deep reinforcement learning agents solving high-dimensional
environments * Cutting-edge agents that emulate human-like behavior
and techniques for artificial general intelligence Deep
reinforcement learning is a form of machine learning in which AI
agents learn optimal behavior on their own from raw sensory input.
The system perceives the environment, interprets the results of its
past decisions and uses this information to optimize its behavior
for maximum long-term return.
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