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Deep Learning and Physics (Hardcover, 1st ed. 2021)
Loot Price: R3,363
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Deep Learning and Physics (Hardcover, 1st ed. 2021)
Series: Mathematical Physics Studies
Expected to ship within 10 - 15 working days
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What is deep learning for those who study physics? Is it completely
different from physics? Or is it similar? In recent years, machine
learning, including deep learning, has begun to be used in various
physics studies. Why is that? Is knowing physics useful in machine
learning? Conversely, is knowing machine learning useful in
physics? This book is devoted to answers of these questions.
Starting with basic ideas of physics, neural networks are derived
naturally. And you can learn the concepts of deep learning through
the words of physics. In fact, the foundation of machine learning
can be attributed to physical concepts. Hamiltonians that determine
physical systems characterize various machine learning structures.
Statistical physics given by Hamiltonians defines machine learning
by neural networks. Furthermore, solving inverse problems in
physics through machine learning and generalization essentially
provides progress and even revolutions in physics. For these
reasons, in recent years interdisciplinary research in machine
learning and physics has been expanding dramatically. This book is
written for anyone who wants to learn, understand, and apply the
relationship between deep learning/machine learning and physics.
All that is needed to read this book are the basic concepts in
physics: energy and Hamiltonians. The concepts of statistical
mechanics and the bracket notation of quantum mechanics, which are
explained in columns, are used to explain deep learning frameworks.
We encourage you to explore this new active field of machine
learning and physics, with this book as a map of the continent to
be explored.
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