Bandit Algorithms for Website Optimization (Paperback)
John Myles White
- 出版商: O'Reilly
- 出版日期: 2013-01-29
- 售價: $1,010
- 貴賓價: 9.5 折 $960
- 語言: 英文
- 頁數: 88
- 裝訂: Paperback
- ISBN: 1449341330
- ISBN-13: 9781449341336
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相關分類:
Algorithms-data-structures
海外代購書籍(需單獨結帳)
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相關主題
商品描述
When looking for ways to improve your website, how do you decide which changes to make? And which changes to keep? This concise book shows you how to use Multiarmed Bandit algorithms to measure the real-world value of any modifications you make to your site. Author John Myles White shows you how this powerful class of algorithms can help you boost website traffic, convert visitors to customers, and increase many other measures of success.
This is the first developer-focused book on bandit algorithms, which were previously described only in research papers. You’ll quickly learn the benefits of several simple algorithms—including the epsilon-Greedy, Softmax, and Upper Confidence Bound (UCB) algorithms—by working through code examples written in Python, which you can easily adapt for deployment on your own website.
- Learn the basics of A/B testing—and recognize when it’s better to use bandit algorithms
- Develop a unit testing framework for debugging bandit algorithms
- Get additional code examples written in Julia, Ruby, and JavaScript with supplemental online materials
商品描述(中文翻譯)
在尋找改善網站的方法時,您如何決定要進行哪些更改?以及要保留哪些更改?這本簡明的書向您展示如何使用多臂搶劫算法來衡量您對網站所做任何修改的真實價值。作者約翰·邁爾斯·懷特(John Myles White)向您展示這個強大的算法類別如何幫助您提高網站流量,將訪問者轉化為客戶,並增加其他許多成功指標。
這是關於搶劫算法的第一本針對開發者的書籍,以前只在研究論文中有描述。通過在Python中編寫的代碼示例,您將迅速了解幾種簡單算法的好處,包括epsilon-Greedy、Softmax和Upper Confidence Bound(UCB)算法,您可以輕鬆適應並部署到自己的網站上。
學習A/B測試的基礎知識,並了解何時最好使用搶劫算法
開發用於調試搶劫算法的單元測試框架
獲取使用Julia、Ruby和JavaScript編寫的其他代碼示例,以及補充的在線資料