Erschienen: 10.12.2012 Abbildung von White | Bandit Algorithms for Website Optimization | 2012
eBook

White

Bandit Algorithms for Website Optimization

2012. eBook , eBook. 88 S. PDF

O'Reilly Media. ISBN 978-1-4493-4159-6

In englischer Sprache

Das Werk ist Teil der Reihe: O'Reilly Media

Produktbeschreibung

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. Youll quickly learn the benefits of several simple algorithmsincluding the epsilon-Greedy, Softmax, and Upper Confidence Bound (UCB) algorithmsby working through code examples written in Python, which you can easily adapt for deployment on your own website.Learn the basics of A/B testingand recognize when its better to use bandit algorithmsDevelop a unit testing framework for debugging bandit algorithmsGet additional code examples written in Julia, Ruby, and JavaScript with supplemental online materials

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