Bandit Algorithms for Website Optimization: Developing, Deploying and Debugging - Softcover

White, John Myles

Softcover

ISBN 10: 1449341330 ISBN 13: 9781449341336

Verlag: O'Reilly and Associates, 2013

Inhaltsangabe

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

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Über die Autorin bzw. den Autor

John Myles White is a PhD candidate in Psychology at Princeton. He studies pattern recognition, decision-making, and economic behavior using behavioral methods and fMRI. He is particularly interested in anomalies of value assessment.

Details zur Ausgabe

• Verlag: O'Reilly and Associates
• Erscheinungsdatum: 2013
• Sprache: Englisch
• ISBN 10: 1449341330
• ISBN 13: 9781449341336
• Einband: Taschenbuch
• Auflage: 1
• Anzahl der Seiten: 88
• Kontakt zum Hersteller: O'Reilly; https://oreilly.com; ; 1005 Gravenstein Highway North; Sebastopol; CA; 95472; USA
• Verantwortliche Person: preigu; mail@preigu.de; ; Lengericher Landstr. 19; Osnabrück; 49078; Deutschland