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Machine Learning with Core ML

You're reading from   Machine Learning with Core ML An iOS developer's guide to implementing machine learning in mobile apps

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Product type Paperback
Published in Jun 2018
Publisher Packt
ISBN-13 9781788838290
Length 378 pages
Edition 1st Edition
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Author (1):
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Joshua Newnham Joshua Newnham
Author Profile Icon Joshua Newnham
Joshua Newnham
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Table of Contents (12) Chapters Close

Preface 1. Introduction to Machine Learning FREE CHAPTER 2. Introduction to Apple Core ML 3. Recognizing Objects in the World 4. Emotion Detection with CNNs 5. Locating Objects in the World 6. Creating Art with Style Transfer 7. Assisted Drawing with CNNs 8. Assisted Drawing with RNNs 9. Object Segmentation Using CNNs 10. An Introduction to Create ML 11. Other Books You May Enjoy

Inference on the edge

For those unfamiliar with the term edge computing, it simply refers to computation performed at the end, or edge, of a network as opposed to sending it to a central server for computation. Some examples of edge devices include cars, robots, Internet of Things (IoT), and, of course, smartphones. 

The motivation for performing computation at the edge, where the data resides, is that sending data across the network is expensive and time-consuming; this incurred latency and cost restrict us with what experiences we can deliver to the user. Removing these barriers opens up new applications that would otherwise not be possible. Another benefit of performing inference at the edge is data privacy; removing the need of having to transmit personal data across the network reduces the opportunities that a malicious user has for obtaining it.

Luckily, technology...

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