Machine Learning for Mobile

Book Description

Leverage the power of machine learning on mobiles and build intelligent mobile applications with ease

Key Features

• Build smart mobile applications for Android and iOS devices
• Use popular machine learning toolkits such as Core ML and TensorFlow Lite
• Explore cloud services for machine learning that can be used in mobile apps

Book Description

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.

What you will learn

• Build intelligent machine learning models that run on Android and iOS
• Use machine learning toolkits such as Core ML, TensorFlow Lite, and more
• Learn how to use Google Mobile Vision in your mobile apps
• Build a spam message detection system using Linear SVM
• Using Core ML to implement a regression model for iOS devices
• Build image classification systems using TensorFlow Lite and Core ML

Who this book is for

If you are a mobile app developer or a machine learning enthusiast keen to use machine learning to build smart mobile applications, this book is for you. Some experience with mobile application development is all you need to get started with this book. Prior experience with machine learning will be an added bonus

Table of Contents

1. Introduction to Machine Learning on Mobile
2. Supervised and Unsupervised Learning Algorithms
3. Random Forest on iOS
4. Tensor Flow Mobile in Android
5. Regression Using CoreML in iOS
6. ML Kit and Image Labelling
7. Spam Message Detection in iOS – CoreML
8. Fritz – iOS and Android
9. Neural Networks on Mobile
10. Mobile Application using Google Cloud Vision
11. Future of ML on Mobile Applications
12. Appendix

中文：

书名：移动环境下的机器学习

利用移动设备上的机器学习功能，轻松构建智能移动应用程序

主要特点

• 为Android和iOS设备构建智能移动应用
• 使用流行的机器学习工具包，如Core ML和TensorFlow Lite
• 探索可在移动应用程序中使用的机器学习云服务

Book Description

机器学习在软件开发中提供了一个完全独特的机会。它允许智能手机产生大量有用的数据，这些数据可以被挖掘、分析并用于预测。这本书将帮助你掌握机器学习的移动设备与易于遵循，实用的例子。

你将从介绍移动设备上的机器学习开始，并掌握基础知识，这样你就会非常熟悉这门学科。您将掌握监督和非监督学习算法，然后学习如何在Android和iOS平台上使用基于移动的库(如Core ML、TensorFlow Lite、ML Kit和Fritz)构建机器学习模型。在这样做的过程中，您还将解决与计算机视觉和其他真实世界领域相关的一些常见和不常见的机器学习问题。

到本书结束时，您将深入探讨机器学习并轻松实现设备上的机器学习，从而彻底了解如何在您的移动设备上运行、创建和构建实时机器学习应用程序。

What you will learn

• 构建在Android和iOS上运行的智能机器学习模型
• 使用机器学习工具包，如Core ML、TensorFlow Lite等
• 了解如何在您的移动应用程序中使用Google Mobile Vision
• 利用线性支持向量机构建垃圾短信检测系统
• 使用Core ML实现iOS设备的回归模型
• Build image classification systems using TensorFlow Lite and Core ML

Who this book is for

如果你是一名移动应用程序开发人员或机器学习爱好者，热衷于使用机器学习来构建智能移动应用程序，这本书适合你。掌握一些移动应用程序开发的经验就可以开始阅读这本书了。有机器学习经验者优先。

Table of Contents

1. Introduction to Machine Learning on Mobile
2. 监督和非监督学习算法
3. Random Forest on iOS
4. Android中的张量流移动
5. 在iOS中使用CoreML进行回归
6. ML试剂盒和图像标签
7. Spam Message Detection in iOS – CoreML
8. Fritz-iOS和Android
9. 移动环境下的神经网络
10. Mobile Application using Google Cloud Vision
11. Future of ML on Mobile Applications
12. 附录