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Deep Learning and Physics (Hardcover, 1st ed. 2021) Loot Price: R3,477
Discovery Miles 34 770
Deep Learning and Physics (Hardcover, 1st ed. 2021): Akinori Tanaka, Akio Tomiya, Koji Hashimoto

Deep Learning and Physics (Hardcover, 1st ed. 2021)

Akinori Tanaka, Akio Tomiya, Koji Hashimoto

Series: Mathematical Physics Studies

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Loot Price R3,477 Discovery Miles 34 770 | Repayment Terms: R326 pm x 12*

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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.

General

Imprint: Springer Verlag, Singapore
Country of origin: Singapore
Series: Mathematical Physics Studies
Release date: February 2021
First published: 2021
Authors: Akinori Tanaka • Akio Tomiya • Koji Hashimoto
Dimensions: 235 x 155mm (L x W)
Format: Hardcover
Pages: 207
Edition: 1st ed. 2021
ISBN-13: 978-981-3361-07-2
Categories: Books > Science & Mathematics > Physics > General
Books > Science & Mathematics > Mathematics > Applied mathematics > General
Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
LSN: 981-3361-07-7
Barcode: 9789813361072

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