Deep Learning and the Game of Go
暫譯: 深度學習與圍棋遊戲

Max Pumperla, Kevin Ferguson

  • 出版商: Manning
  • 出版日期: 2019-01-25
  • 定價: $1,980
  • 售價: 8.8$1,742 (限時優惠至 2025-03-31)
  • 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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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)

使用圍棋作為教學機器學習的方式,既具啟發性又令人鼓舞。強烈推薦!

- Burk Hufnagel, Daugherty Business Solutions

《深度學習與圍棋》教你如何將深度學習的力量應用於複雜的推理任務,透過建立一個圍棋 AI。首先,你將接觸機器學習和深度學習的基礎,然後使用 Python 建立一個機器人,並教它遊戲規則。

關於技術

古老的策略遊戲圍棋是人工智慧的一個驚人案例研究。在2016年,一個基於深度學習的系統震驚了圍棋界,擊敗了一位世界冠軍。隨後,升級版的 AlphaGo Zero 利用深度強化學習掌握了這個遊戲,徹底擊潰了原始的機器人。現在,你可以透過建立自己的圍棋機器人來學習這些相同的深度學習技術!

關於本書

《深度學習與圍棋》通過教你建立一個圍棋獲勝機器人來介紹深度學習。隨著進展,你將使用 Python 深度學習庫 Keras 應用越來越複雜的訓練技術和策略。你將享受觀看你的機器人掌握圍棋的過程,並在此過程中發現如何將你的新深度學習技能應用於各種其他場景!

內容概覽

- 建立並教導一個自我改善的遊戲 AI
- 使用深度學習增強經典遊戲 AI 系統
- 實現深度學習的神經網絡

關於讀者

你只需要基本的 Python 技能和高中數學水平的知識。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,擅長分散式系統和數據科學。Max 和 Kevin 一起建立了開源機器人 BetaGo。

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