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Machine Learning for Mobile
By :
Machine Learning for Mobile
By:
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
Free Chapter
Introduction to Machine Learning on Mobile
Supervised and Unsupervised Learning Algorithms
Random Forest on iOS
TensorFlow Mobile in Android
Regression Using Core ML in iOS
The ML Kit SDK
Spam Message Detection
Neural Networks on Mobile
Mobile Application Using Google Vision
The Future of ML on Mobile Applications
Question and Answers
Other Books You May Enjoy
Index
Customer Reviews