Pumperla, Ferguson -- Deep Learning and the Game of Go -- 2019 pdf torrent

Deep Learning and the Game of Go
Authors: Max Pumperla, Kevin Ferguson


Genres
Artificial Intelligence
Go
Computer Science

Description:
Summary

Deep Learning and the Game of Go teaches you how to apply the power of deep learning to complex reasoning tasks by building a Go-playing AI. After exposing you to the foundations of machine and deep learning, you'll use Python to build a bot and then teach it the rules of the game.

Foreword by Thore Graepel, DeepMind

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

About the Technology

The ancient strategy game of Go is an incredible case study for AI. In 2016, a deep learning-based system shocked the Go world by defeating a world champion. Shortly after that, the upgraded AlphaGo Zero crushed the original bot by using deep reinforcement learning to master the game. Now, you can learn those same deep learning techniques by building your own Go bot!

About the Book

Deep Learning and the Game of Go introduces deep learning by teaching you to build a Go-winning bot. As you progress, you'll apply increasingly complex training techniques and strategies using the Python deep learning library Keras. You'll enjoy watching your bot master the game of Go, and along the way, you'll discover how to apply your new deep learning skills to a wide range of other scenarios!

What's inside
About the Reader

All you need are basic Python skills and high school-level math. No deep learning experience required.

About the Author

Max Pumperla and Kevin Ferguson are experienced deep learning specialists skilled in distributed systems and data science. Together, Max and Kevin built the open source bot BetaGo.

Table of Contents

Goodreads page:
https://www.goodreads.com/book/show/37419955-deep-learning-and-the-game-of-go

Please note that this description is auto-generated by a bot, if you find the description incorrect then please report in the comments. Description will be edited accordingly afterwards.