This manual provides comprehensive guidance for "Bandit Algorithms for Website Optimization," authored by John Myles White and published by O'Reilly Media on December 10, 2012. This developer-focused book delves into the application of Multiarmed Bandit algorithms for enhancing website performance. It covers essential topics such as A/B testing, the implementation of various bandit algorithms including Epsilon-Greedy, Softmax, and Upper Confidence Bound (UCB), and the use of a unit testing framework for debugging. The primary benefit highlighted is the ability to measure the real-world value of website modifications, with secondary benefits including boosting website traffic and converting visitors into customers. The content is derived from research papers and explores the use of Python, with supplemental discussions in Julia, Ruby, and JavaScript.
The purpose of this manual is to equip developers with the knowledge and tools necessary to effectively implement bandit algorithms for website optimization. It details how to leverage these techniques to improve user engagement and business outcomes. The manual covers the theoretical underpinnings and practical applications of these algorithms, offering insights into their development and deployment. It serves as a crucial resource for understanding and applying advanced optimization strategies to digital platforms, ultimately aiming to enhance user experience and achieve measurable improvements in website performance and conversion rates.
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
Author: White, John Myles
Publisher: O'Reilly Media
Illustration: N
Language: ENG
Title: Bandit Algorithms for Website Optimization
Pages: 00088 (Unencrypted EPUB)
On Sale: 2012-12-10
SKU-13/ISBN: 9781449341336
Category: Computers : Programming - Algorithms
Category: Computers : Programming Languages - Python
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
Author: White, John Myles
Publisher: O'Reilly Media
Illustration: N
Language: ENG
Title: Bandit Algorithms for Website Optimization
Pages: 00088 (Unencrypted EPUB)
On Sale: 2012-12-10
SKU-13/ISBN: 9781449341336
Category: Computers : Programming - Algorithms
Category: Computers : Programming Languages - Python
