Book Image

Machine Learning for Mobile

By : Revathi Gopalakrishnan, Avinash Venkateswarlu
Book Image

Machine Learning for Mobile

By: Revathi Gopalakrishnan, Avinash Venkateswarlu

Overview of this book

Machine learning presents an entirely unique opportunity in software development. It allows smartphones to produce an enormous amount of useful data that can be mined, analyzed, and used to make predictions. This book will help you master machine learning for mobile devices with easy-to-follow, practical examples. You will begin with an introduction to machine learning on mobiles and grasp the fundamentals so you become well-acquainted with the subject. You will master supervised and unsupervised learning algorithms, and then learn how to build a machine learning model using mobile-based libraries such as Core ML, TensorFlow Lite, ML Kit, and Fritz on Android and iOS platforms. In doing so, you will also tackle some common and not-so-common machine learning problems with regard to Computer Vision and other real-world domains. By the end of this book, you will have explored machine learning in depth and implemented on-device machine learning with ease, thereby gaining a thorough understanding of how to run, create, and build real-time machine-learning applications on your mobile devices.
Table of Contents (19 chapters)
Title Page
Copyright and Credits
About Packt
Contributors
Preface
Question and Answers
Index

Understanding ML Kit


ML Kit encompasses all the existing Google offerings for machine learning on mobile. It bundles the Google Cloud Vision API, TensorFlow Lite, and the Android Neural Networks API together in a single SDK, as shown:

ML Kit enables developers to utilize machine learning in their mobile applications for both Android and iOS apps, in a very easy way. Inference can be carried out by invoking APIs that are either on-device or on-cloud.

The advantages of on-device APIs are that they work completely offline, and are more secure as no data is sent to the cloud. By contrast, on-cloud APIs do require network connectivity, and do send data off-device, but allow for greater accuracy.

ML Kit offers APIs covering the following machine learning scenarios that may be required by mobile application developers:

  • Image labeling
  • Text recognition
  • Landmark detection
  • Face detection
  • Barcode scanning 

All these APIs are implemented using complex machine learning algorithms. However, those details are wrapped...