Deep Learning and the Game of Go

Max Pumperla, Kevin Ferguson

Deep Learning and the Game of Go
  • 出版商: Manning
  • 出版日期: 2019-01-25
  • 售價: $1,980
  • 貴賓價: 9.5 折 $1,881
  • 語言: 英文
  • 頁數: 384
  • 裝訂: Paperback
  • ISBN: 1617295329
  • ISBN-13: 9781617295324
  • 相關分類: DeepLearning
  • 相關翻譯: 深度學習與圍棋 (簡中版)

    • 立即出貨

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商品描述(中文翻譯)


 


作者簡介

Using the game of Go as a way to teach machine learning is inspired and inspiring. Highly recommended!

-  Burk Hufnagel, Daugherty Business Solutions

 

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 the machine and deep learning, you'll use Python to build a bot and then teach it the rules of the game.

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

  • Build and teach a self-improving game AI
  • Enhance classical game AI systems with deep learning
  • Implement neural networks for deep learning

about the reader

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

about the authors

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.

作者簡介(中文翻譯)

「以圍棋作為教授機器學習的方式是一個啟發且具啟發性的方法。強烈推薦！」- Burk Hufnagel, Daugherty Business Solutions

《深度學習與圍棋》教導您如何應用深度學習的力量來解決複雜的推理任務，並建立一個能下圍棋的人工智慧。在介紹機器學習和深度學習的基礎後，您將使用Python來建立一個機器人，並教它遵守遊戲規則。

關於技術方面，古老的圍棋遊戲是人工智慧的一個令人難以置信的案例研究。2016年，一個基於深度學習的系統通過擊敗世界冠軍震驚了圍棋界。不久之後，升級版的AlphaGo Zero通過使用深度強化學習來掌握遊戲，輕易擊敗了原始機器人。現在，您可以通過建立自己的圍棋機器人來學習這些深度學習技術！

本書《深度學習與圍棋》通過教授您建立一個能贏得圍棋的機器人來介紹深度學習。隨著學習的進展，您將使用Python深度學習庫Keras來應用越來越複雜的訓練技巧和策略。您將樂在觀察您的機器人掌握圍棋的過程中，同時，您還將發現如何將您的新深度學習技能應用於各種其他情境！

本書的內容包括：
- 建立並教導一個自我改進的遊戲人工智慧
- 使用深度學習增強傳統遊戲人工智慧系統
- 實現用於深度學習的神經網絡

讀者只需要具備基本的Python技能和高中程度的數學知識，無需深度學習經驗。

關於作者：
Max Pumperla和Kevin Ferguson是經驗豐富的深度學習專家，擅長分散系統和數據科學。Max和Kevin共同建立了開源機器人BetaGo。

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