Leverage the power of Apple's Core ML to create smart iOS apps
Explore the concepts of machine learning and Apple's Core ML APIs
Use Core ML to understand and transform images and videos
Exploit the power of using CNN and RNN in iOS applications
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
What you will learn
Understand components of an ML project using algorithms, problems, and data
Master Core ML by obtaining and importing machine learning model, and generate classes
Prepare data for machine learning model and interpret results for optimized solutions
Create and optimize custom layers for unsupported layers
Apply CoreML to image and video data using CNN
Learn the qualities of RNN to recognize sketches, and augment drawing
Use Core ML transfer learning to execute style transfer on images
Who this book is for
Machine Learning with Core ML is for you if you are an intermediate iOS developer interested in applying machine learning to your mobile apps. This book is also for those who are machine learning developers or deep learning practitioners who want to bring the power of neural networks in their iOS apps. Some exposure to machine learning concepts would be beneficial but not essential, as this book acts as a launchpad into the world of machine learning for developers.
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