Hands-On Artificial Intelligence for Android: Understand Machine Learning and Unleash the Power of TensorFlow in Android Applications with Google ML Kit Paperback – 28 February 2022

This book features techniques and real implementations of machine learning applications on Android phones. This

book covers various developer tools, including TensorFlow and Google ML Kit.

The book begins with a quick review of android application development fundamentals and a couple of Java and Kotlin implementations developed using the Android Studio integrated development environment. The book explores TensorFlow Lite and Google ML Kit, along with some of the most widely used machine learning techniques. The book covers real projects on TensorFlow, demonstrates how to collect photos with Camera X, and preprocess them with the Google ML Kit. It explains how to onboard the power of machine learning in Android applications that detect images, identify faces, and apply effects to photographs, among other things. These applications are constructed on top of TensorFlow models – some of which were created and trained by the reader – and then converted to TensorFlow Lite for mobile applications.

After reading the book, the reader will be able to apply machine learning techniques to create Android applications and take their applications to the next level. This book can be a successful tool to deep dive into Data Science for all mobile programmers.

TABLE OF CONTENTS

1. Building an Application with Android Studio and Java

2. Event Handling and Intents in Android

3. Building our Base Application with Kotlin and SQLite

4. An Overview of Artificial Intelligence and Machine Learning

5. Introduction to TensorFlow

6. Training a Model for Image Recognition with TensorFlow

7. Android Camera Image Capture with CameraX

8. Using the Image Recognition Model in an Android Application

9. Detecting Faces with the Google ML Kit

10. Verifying Faces in Android with TensorFlow Lite

11. Registering Faces in the Application

12. Image Processing with Generative Adversarial Networks

13. Describing Images with NLP