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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 saw how we can build a cross-platform app using Flutter with an authentication system powered by Firebase, while incorporating the benefits of deep learning. We then understood how hacking attempts can be classified as anomalies in general user behavior, and created a model to sort these anomalies out to prevent malicious users from logging in. Finally, we used ReCaptcha by Google to remove spammy use of the app, and hence make it more resilient in relation to automated spam or scripted hacking attacks.

In the next chapter, we will explore a very interesting project – transcript generation of music using deep learning on mobile apps.

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