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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

Learning algorithms 

In Chapter 1Introduction to Machine Learning, we saw many different types of learning algorithms and learned that ML is really a process of automatically discovering rules given a set of examples. The main components required for this process, specifically for supervised learning, include: 

  • Input data points: For image classification, we would require images of the domain we want to classify, for example, animals. 
  • The expected outputs for these inputs: Continuing from our previous example of image classification of animals, the expected outputs could be labels associated with each of the images, for example, cat, dog, and many more. 
  • A ML algorithm: This is the algorithm used to automatically learn how to transform the input data points into a meaningful output. These derived sets of rules are what we call the...
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