Hands-On Artificial Intelligence for Android

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.

KEY FEATURES

* Learn by doing, training, and evaluating your own machine learning models.
* Includes pre-trained TensorFlow models for image processing.
* Explains practical use cases of artificial intelligence in Android.

WHAT YOU WILL LEARN

* Get well-versed with Android Development and the fundamentals of AI.
* Learn to set up the ML environment with hands-on knowledge of TensorFlow.
* Build, train, and evaluate Machine Learning models.
* Practice ML by working on real face verification and identification applications.
* Explore cutting-edge models such as GAN and RNN in detail.
* Experience the use of CameraX, SQLite, and Google ML Kit on Android.

WHO THIS BOOK IS FOR

This book is intended for android developers, application engineers, machine learning engineers, and anybody interested in infusing intelligent, inventive, and smart features into mobile phones. Readers should have a basic understanding of the Java programming language.

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

Vasco Correia Veloso has been developing software for over 20 years. From assembly to Java and Kotlin, on big and small computers, from floppy disks to SSDs, on-premises, and cloud, he’s been there and done that. He loves to learn how things work and tell others what he finds. The field of AI has spiked his curiosity since HAL 9000 appeared on the silver screen.

LinkedIn Profile: Vasco Correia Veloso

Blog Link: https://www.infoq.com/profile/Vasco-Veloso/, https://medium.com/@vasco-veloso