| Description |
xiii, 290 pages : illustrations ; 24 cm |
| Bibliography |
Includes bibliographical references (pages 269-281) and index |
| Contents |
Chapter 1: Machine Learning Basics -- Chapter 2: Essential Math -- Chapter 3: Differential Programming -- Chapter 4: TensorFlow Basics -- Chapter 5: Neural Networks -- Chapter 6: Computer Vision |
| Summary |
Discover more insight about deep learning and how to work with Swift for TensorFlow to develop intelligent apps. TensorFlow was designed for easy adoption by iOS programmers working in Swift. This book covers the established and tested concepts and ties thme to modern Swift programming and applicable use in developing for iOS. Using illustrative examples, the book starts off by introducing you to basic machine learning concepts along with code snippets in Swift for TensorFlow. Fundamentals of neural networks required to understand today's deep learning research will be covered and put in the context of working in the Swift language with the goal of developing primarily for Apple's mobile ecosystem. Other important topics covered include computation graphs, loss functions, optimization techniques, regulazrizing nueral networks, recurrent neural networks-- such as those used in Siri and Google Translate; and convolutional neural networks. You'll also learn to reuse pre-trained neural networks and work with generative models. Finally, developing and building in security to models in addressed. Swift code will be provided throughout the book to keep the concepts grounded in application within Apple's frameworks. You will: write machine learning code in Swift ; Run neural networks in Apple environments ; Apply fundamental deep learning concepts to mobile app development |
| Subject |
TensorFlow.
|
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Swift (Computer program language)
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Machine learning.
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Artificial intelligence.
|
| ISBN |
9781484263297 |
|
1484263294 |
|
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