Book Image

Machine Learning with Core ML

Book Image

Machine Learning with Core ML

Overview of this book

Core ML is a popular framework by Apple, with APIs designed to support various machine learning tasks. It allows you to train your machine learning models and then integrate them into your iOS apps. Machine Learning with Core ML is a fun and practical guide that not only demystifies Core ML but also sheds light on machine learning. In this book, you’ll walk through realistic and interesting examples of machine learning in the context of mobile platforms (specifically iOS). You’ll learn to implement Core ML for visual-based applications using the principles of transfer learning and neural networks. Having got to grips with the basics, you’ll discover a series of seven examples, each providing a new use-case that uncovers how machine learning can be applied along with the related concepts. By the end of the book, you will have the skills required to put machine learning to work in their own applications, using the Core ML APIs
Table of Contents (16 chapters)
Title Page
Packt Upsell
Contributors
Preface
Index

Appendix 1. Other Books You May Enjoy

If you enjoyed this book, you may be interested in these other books by Packt:

Mastering Machine Learning Algorithms Giuseppe Bonaccorso

ISBN: 978-1-78862-111-3

  • Explore how a ML model can be trained, optimized, and evaluated
  • Understand how to create and learn static and dynamic probabilistic models
  • Successfully cluster high-dimensional data and evaluate model accuracy
  • Discover how artificial neural networks work and how to train, optimize, and validate them
  • Work with Autoencoders and Generative Adversarial Networks
  • Apply label spreading and propagation to large datasets
  • Explore the most important Reinforcement Learning techniques

Machine Learning with Swift Alexander Sosnovshchenko

ISBN: 978-1-78712-151-5

  • Learn rapid model prototyping with Python and Swift
  • Deploy pre-trained models to iOS using Core ML
  • Find hidden patterns in the data using unsupervised learning
  • Get a deeper understanding of the clustering techniques
  • Learn modern compact architectures of neural networks for iOS devices
  • Train neural networks for image processing and natural language processing