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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 2. Introduction to Apple Core ML FREE CHAPTER 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

Input data and preprocessing 


In this section, we will implement the preprocessing functionality required to transform our raw user input into something the model is expecting. We will build up this functionality in a playground project before migrating it across to our project in the next section.  

If you haven't done so, pull down the latest code from the accompanying repository https://github.com/PacktPublishing/Machine-Learning-with-Core-ML. Once downloaded, navigate to the directory Chapter8/Start/ and open the playground project ExploringQuickDrawData.playground. Once loaded, you will see the playground for this chapter, as shown:

The playground includes a few samples of the raw Quick, Draw! dataset, a single simplified extract, as well as the complied model and supporting classes we created in the previous chapter to represent a sketch (Stroke.swift, Sketch.swift) and render it (SketchView.swift). Our goal for this section will be to better understand the data and the preprocessing...

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