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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

Developing a GCP-hosted REST API for the chess engine

Now that we have seen how we will be moving ahead with this project, we also need to discuss how we're going to map the game of Connect 4 to chess and deploy a chess RL engine as an API. 

You can find the files we've created for this chess engine at https://github.com/PacktPublishing/Mobile-Deep-Learning-Projects/tree/master/Chapter8/chess. Let's quickly understand some of the most important files before we map these files with those in the Connect 4 project: 

  • src/chess_zero/agent/:
  • player_chess.py: This file describes the ChessPlayer class, which holds information about the players playing the game at any point in time. It provides wrappers for the methods associated with searching for new moves using the Monte Carlo tree search, changing the player state, and other functions required during...
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