This book will help you perform machine learning on mobile with simple practical examples. You start from the basics of machine learning, and by the time you complete the book, you will have a good grasp of what mobile machine learning is and what tools/SDKs are available for implementing mobile machine learning, and will also be able to implement various machine learning algorithms in mobile applications that can be run in both iOS and Android.

You will learn what machine learning is and will understand what is driving mobile machine learning and how it is unique. You will be exposed to all the mobile machine learning tools and SDKs: TensorFlow Lite, Core ML, ML Kit, and Fritz on Android and iOS. This book will explore the high-level architecture and components of each toolkit. By the end of the book, you will have a broad understanding of machine learning models and will be able to perform on-device machine learning. You will get deep-dive insights into machine learning algorithms such as regression, classification, linear support vector machine (SVM), and random forest. You will learn how to do natural language processing and implement spam message detection. You will learn how to convert existing models created using Core ML and TensorFlow into Fritz models. You will also be exposed to neural networks. You will also get sneak peek into the future of machine learning, and the book also contains an FAQ section to answer all your queries on mobile machine learning. It will help you to build an interesting diet application that provides the calorie values of food items that are captured on a camera, which runs both in iOS and Android.