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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

Reinforcement learning in mobile games

Reinforcement learning has gained popularity among developers who wish to build game-playing AIs for various reasons – to simply check the capabilities of the AI, to build a training agent that helps professionals improve their game, and so on. From a researcher's point of view, games offer the best testing environment for reinforcement learning agents that can make decisions based on experience and learn to survive/achieve in any given environment. This is due to the fact that games can be designed with simple and precise rules, where the reaction of the environment to a certain action can be accurately predicted. This makes it easier to evaluate the performance of the reinforcement learning agents, and thereby facilitate a good training ground for the AI. With the breakthroughs in game-playing AIs taken into consideration, it...

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