Bandit Algorithms for Website Optimization pdf epub mobi txt 电子书下载 2024

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简体网页||繁体网页

John Myles White

O'Reilly Media

2013-1-3

USD 19.99

Paperback

9781449341336

图书标签: Algorithms 算法 Optimization Bandit Website 计算机科学计算机机器学习

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发表于2024-12-27

Bandit Algorithms for Website Optimization epub 下载 mobi 下载 pdf 下载 txt 电子书下载 2024

Bandit Algorithms for Website Optimization pdf epub mobi txt 电子书下载 2024

图书描述

This book shows you how to run experiments on your website using A/B testing - and then takes you a huge step further by introducing you to bandit algorithms for website optimization. Author John Myles White shows you how this family 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 have previously only been described in research papers. You'll learn about several simple algorithms you can deploy on your own websites to improve your business including the epsilon-greedy algorithm, the UCB algorithm and a contextual bandit algorithm. All of these algorithms are implemented in easy-to-follow Python code and be quickly adapted to your business's specific needs. You'll also learn about a framework for testing and debugging bandit algorithms using Monte Carlo simulations, a technique originally developed by nuclear physicists during World War II. Monte Carlo techniques allow you to decide whether A/B testing will work for your business needs or whether you need to deploy a more sophisticated bandits algorithm.

Bandit Algorithms for Website Optimization 下载 mobi epub pdf txt 电子书

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Bandit Algorithms for Website Optimization pdf epub mobi txt 电子书下载

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用户评价

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比论文简单，比网上的文章全面，还算比较实用

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非常入门

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太水啦还给我讲人生经验

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初学入门4星，深入理解2星。Steven L. Scott的A modern Bayesian look at the mult-armed bandit可以参考着看。

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pros:作为一个教材写得很成功，循序渐进，从最初的问题开始，提出解决方案，指出不足，迭代出新方案；解释得很清晰。cons:没有理论基础；作者的Python代码水平一般般

读后感

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multiarmed bandit原本是从赌场中的多臂老虎机的场景中提取出来的数学模型。是无状态（无记忆）的reinforcement learning。目前应用在operation research，机器人，网站优化等领域。 arm：指的是老虎机（slot machine）的拉杆。 bandit：多个拉杆的集合，bandit = {arm1, ar...

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