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Deep Learning with Swift for TensorFlow

Jezik AngleščinaAngleščina
Knjiga Mehka
Knjiga Deep Learning with Swift for TensorFlow Rahul Bhalley
Koda Libristo: 33064544
Založba APress, januar 2021
About this book Discover more insight about deep learning algorithms with Swift for T... Celoten opis
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About this book Discover more insight about deep learning algorithms with Swift for TensorFlow. The Swift language was designed by Apple for optimized performance and development whereas TensorFlow library was designed by Google for advanced machine learning research. Swift for TensorFlow is a combination of both with support for modern hardware accelerators and more. This book covers the deep learning concepts from fundamentals to advanced research. It also introduces the Swift language for beginners in programming. This book is well suited for newcomers and experts in programming and deep learning alike. After reading this book you should be able to program various state-of-the-art deep learning algorithms yourself. The book covers foundational concepts of machine learning. It also introduces the mathematics required to understand deep learning. Swift language is introduced such that it allows beginners and researchers to understand programming and easily transit to Swift for TensorFlow, respectively. You will understand the nuts and bolts of building and training neural networks, and build advanced algorithms. What You'll Learn - Understand deep learning concepts - Program various deep learning algorithms - Run the algorithms in cloud Who This Book Is For - Newcomers to programming and/or deep learning, and experienced developers. - Experienced deep learning practitioners and researchers who desire to work in user space instead of library space with a same programming language without compromising the speed

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O knjigi

Polni naslov Deep Learning with Swift for TensorFlow
Jezik Angleščina
Vezava Knjiga - Mehka
Datum izida 2021
Število strani 290
EAN 9781484263297
ISBN 1484263294
Koda Libristo 33064544
Založba APress
Teža 468
Mere 155 x 235 x 17
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