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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 an Action on Google release

Finally, we're at the stage where we can create a release for our Actions on Google chatbot. But before doing so, it is important to test out the chatbot in the Google Assistant Test Simulator:

  1. Click on the Simulator button on the left navigation pane of the Actions on Google Console to enter the simulator. In the simulator, you'll be shown an interface similar to using Google Assistant on your phone. A suggested input will contain the invocation method for your action. 

 

  1. Enter the invocation for your action in the simulator, which in our case is Talk to Peter Please. This will produce an output from the Default Welcome Intent asking for your name. Upon entering your name as the response, similar to My name is Sammy, you'll be shown your lucky number, like this: 

Now that we know our chatbot is...

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