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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

Product type Book
Published in Apr 2020
Publisher Packt
ISBN-13 9781789611212
Pages 380 pages
Edition 1st Edition
Languages
Authors (2):
Anubhav Singh Anubhav Singh
Profile icon Anubhav Singh
Rimjhim Bhadani Rimjhim Bhadani
Profile icon Rimjhim Bhadani
View More author details
Toc

Table of Contents (13) Chapters close

Preface 1. Introduction to Deep Learning for Mobile 2. Mobile Vision - Face Detection Using On-Device Models 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

Summary

In this chapter, we looked at some of the most common tools that are available for creating chatbots and then proceeded with an in-depth discussion of Dialogflow to understand the basic terminology that's used. We understood how the Dialogflow Console works so that we can create our own Dialogflow agent. We did this by creating an intent that's capable of extracting the user's name and adding it as an integration to Google Assistant so that it can respond with lucky numbers.

After deploying the webhook for Cloud Functions for Firebase and creating Actions on Google release, we created a conversational Flutter application. We learned how to create a conversation application interface and integrated the Dialogflow agent to facilitate deep learning models based on the responses of the chatbot. Finally, we used a Flutter plugin to add speech recognition...

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