Book Image

Mobile Deep Learning with TensorFlow Lite, ML Kit and Flutter

By : Anubhav Singh, Rimjhim Bhadani
Book Image

Mobile Deep Learning with TensorFlow Lite, ML Kit and Flutter

By: Anubhav Singh, Rimjhim Bhadani

Overview of this book

Deep learning is rapidly becoming the most popular topic in the mobile app industry. This book introduces trending deep learning concepts and their use cases with an industrial and application-focused approach. You will cover a range of projects covering tasks such as mobile vision, facial recognition, smart artificial intelligence assistant, augmented reality, and more. With the help of eight projects, you will learn how to integrate deep learning processes into mobile platforms, iOS, and Android. This will help you to transform deep learning features into robust mobile apps efficiently. You’ll get hands-on experience of selecting the right deep learning architectures and optimizing mobile deep learning models while following an application oriented-approach to deep learning on native mobile apps. We will later cover various pre-trained and custom-built deep learning model-based APIs such as machine learning (ML) Kit through Firebase. Further on, the book will take you through examples of creating custom deep learning models with TensorFlow Lite. Each project will demonstrate how to integrate deep learning libraries into your mobile apps, right from preparing the model through to deployment. By the end of this book, you’ll have mastered the skills to build and deploy deep learning mobile applications on both iOS and Android.
Table of Contents (13 chapters)

Exploring Google's DeepMind

DeepMind is probably one of the most prominent names that comes up when you talk about the growth of self-learning artificial intelligence, owing to their groundbreaking research and achievements in the field. Acquired by Google in 2014, DeepMind is currently a wholly-owned subsidiary of Alphabet since the restructuring of Google in 2015. The most notable works of DeepMind include AlphaGo and its successor, Alpha Zero. Let's discuss these projects in greater depth and try to understand what makes them so important in the present day.

AlphaGo

In 2015, AlphaGo became the first piece of computer software to defeat a professional Go player, Lee Sedol, on a 19x19 board. The breakthrough was...