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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

Chatbot Using Actions on Google

In this project, we will cover the implementation of conversational chatbots using Dialogflow API, and how to make them perform different actions on Google Assistant with the help of Actions on Google. This project will provide you with a good understanding of how to build a product that uses engaging voice and text-based conversational interfaces.

We will implement a chatbot that will ask for the user's name and then generate a lucky number for the user. We will also look into how a chatbot can be made available on the Google Assistant platform using Actions on Google.

The following topics will be covered in this chapter: 

  • Understanding the tools available for creating chatbots
  • Creating a Dialogflow account
  • Creating a Dialogflow agent
  • Understanding the Dialogflow Console
  • Creating your first Action on Google
  • Creating Actions on a...
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