Deep learning with Swift for TensorFlow : differentiable programming with Swift / Rahul Bhalley.
2021
Q325.5
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Linked Resource
Online Access
Concurrent users
Unlimited
Authorized users
Authorized users
Document Delivery Supplied
Can lend chapters, not whole ebooks
Details
Title
Deep learning with Swift for TensorFlow : differentiable programming with Swift / Rahul Bhalley.
Author
Bhalley, Rahul, author.
ISBN
9781484263303 (electronic book)
1484263308 (electronic book)
9781484263310 (print)
1484263316
1484263294
9781484263297
1484263308 (electronic book)
9781484263310 (print)
1484263316
1484263294
9781484263297
Published
[Berkeley, California] : Apress, [2021]
Language
English
Description
1 online resource (xiii, 290 pages) : illustrations
Item Number
10.1007/978-1-4842-6330-3 doi
Call Number
Q325.5
Dewey Decimal Classification
006.31
Summary
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.
Note
Includes index.
Access Note
Access limited to authorized users.
Digital File Characteristics
text file
PDF
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed March 8, 2021).
Available in Other Form
Print version: 9781484263297
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Online Access
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Table of Contents
Machine learnign basics
Essential math
Differentiable programming
TensorFlow basics
Neural netowrks
Computer vision.
Essential math
Differentiable programming
TensorFlow basics
Neural netowrks
Computer vision.