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    Machine Learning for Mobile

    Posted By: readerXXI
    Machine Learning for Mobile

    Machine Learning for Mobile
    by Revathi Gopalakrishnan and Avinash Venkateswarlu
    English | 2018 | ISBN: 1788629353 | 264 Pages | True PDF | 11.2 MB

    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

    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