Deep Learning with Swift for TensorFlow
Differentiable Programming with Swift
Authors: Bhalley, Rahul
Free Preview- Understand neural networks from a Swift for TensorFlow perspective
- Learn the fundamental basics of neural networks
- Use Swift to program for Deep Learning, which is being suggested by researchers as a new era’s dominant deep learning language
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- About this book
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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
- About the authors
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Rahul Bhalley is an independent machine intelligence researcher. He was the co-founder of a short-lived deep learning startup in 2018. He has published research papers in areas such as speech processing and generative modeling. He actively contributes to open source projects related to deep learning on GitHub. He has also worked with Apple's Swift and shares Google's vision of making it easy for others to understand deep learning with Swift.
- Table of contents (6 chapters)
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Machine Learning Basics
Pages 1-35
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Essential Math
Pages 37-65
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Differentiable Programming
Pages 67-141
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TensorFlow Basics
Pages 143-169
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Neural Networks
Pages 171-230
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Table of contents (6 chapters)
Bibliographic Information
- Bibliographic Information
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- Book Title
- Deep Learning with Swift for TensorFlow
- Book Subtitle
- Differentiable Programming with Swift
- Authors
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- Rahul Bhalley
- Copyright
- 2021
- Publisher
- Apress
- Copyright Holder
- Rahul Bhalley
- eBook ISBN
- 978-1-4842-6330-3
- DOI
- 10.1007/978-1-4842-6330-3
- Softcover ISBN
- 978-1-4842-6329-7
- Edition Number
- 1
- Number of Pages
- XIII, 290
- Number of Illustrations
- 46 b/w illustrations
- Topics
