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Mobile Deep Learning with TensorFlow Lite, ML Kit and Flutter

You're reading from   Mobile Deep Learning with TensorFlow Lite, ML Kit and Flutter Build scalable real-world projects to implement end-to-end neural networks on Android and iOS

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Product type Paperback
Published in Apr 2020
Publisher Packt
ISBN-13 9781789611212
Length 380 pages
Edition 1st Edition
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Authors (2):
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Rimjhim Bhadani Rimjhim Bhadani
Author Profile Icon Rimjhim Bhadani
Rimjhim Bhadani
Anubhav Singh Anubhav Singh
Author Profile Icon Anubhav Singh
Anubhav Singh
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Table of Contents (13) Chapters Close

Preface 1. Introduction to Deep Learning for Mobile 2. Mobile Vision - Face Detection Using On-Device Models FREE CHAPTER 3. Chatbot Using Actions on Google 4. Recognizing Plant Species 5. Generating Live Captions from a Camera Feed 6. Building an Artificial Intelligence Authentication System 7. Speech/Multimedia Processing - Generating Music Using AI 8. Reinforced Neural Network-Based Chess Engine 9. Building an Image Super-Resolution Application 10. Road Ahead 11. Other Books You May Enjoy Appendix

Creating Actions on a Google project

In this section, we will create an Actions on Google Project and then integrate it with the Google Assistant app. This will allow the chatbot we've built to be accessible through the Google Assistant app, which is available on billions of devices globally.

Let's begin by creating the Actions on Google project:

  1. In your browser, open https://developers.google.com/actions/ to open up the Actions on xGoogle home page, where you can read all about the platform and also be introduced to its documentation.
  2. To proceed to the console, click on the Start Building or Go to Actions Console button. You'll be taken to the Actions on Google console, where you'll be prompted to create a project.
  3. On proceeding with project creation, you'll be able to see a dialogue box, as shown in the following screenshot: 

You...

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