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)

Implementing a Webhook

In this section, we will enable the webhooks for the luckyNum intent and prepare the webhook code for the logic of the luckyNum intent. Follow these steps to do so:

  1. Open the Intent editing page for the luckyNum intent and scroll down to the Fulfillment section. Here, turn on the Enable webhook call for this intent option.

Now, this intent will look for the response to be generated from the webhook.

  1. Open a text editor of your choice to create the code for the webhook so that it's in JavaScript and will run on the Node.js platform provided by Firebase: 
'use strict';

The preceding line ensures that we use a set of coding standards that have been defined in ECMAScript 5 that provide several useful modifications to the JavaScript language, thus making it more secure and less confusing.

  1. Modules in JavaScript are imported into the...