Machine Learning for iOS Developers

Put the power of Apple iOS machine learning (ML) capabilities to work in your apps! Learn what you can achieve with ML!


Machine Learning for iOS Developers introduces the reader to the field of machine learning (ML) in general, and specifically Apple’s offerings for ML. The reader will learn to use Apple’s ML frameworks to implement machine learning in iOS apps. While the reader does not need prior machine learning experience to use this book, the reader is expected to possess intermediate/advanced knowledge of iOS programming with Swift and a basic knowledge of Python to use this book. This book will appeal to both iOS developers and mobile solution architects. Developers will find concrete examples that show them how to integrate machine learning in their iOS Apps. Solution architects will find useful information on the machine learning capabilities of the Apple.

The first section introduces the reader to fundamental machine learning concepts. Readers will learn about the types of machine learning systems, how they are used, and challenges they may face with machine learning solutions. Readers will be presented with a case study that compares a traditional vs a machine learning approach, and will also learn about the differences between implementing machine learning on handsets vs. machine learning as a service (MLaaS). The second section focuses on using Apple’s CoreML framework to build machine learning capabilities into iOS Apps. The reader will learn to use pre-trained models as well as build their own models using CreateML and TuriCreate and use these with CoreML. In this section readers will build apps that can detect objects in images, implement decision tree based models, implement an instance-based machine learning system,  and integrate Scikit-learn  & Keras models with CoreML. Source code examples are provide for downloading.