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

White, John Myles

ISBN 10: 1449341330 / ISBN 13: 9781449341336

Editore: O'Reilly Media, 2013

May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less 0.4. Codice articolo G1449341330I4N00

Riassunto:

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

Informazioni sull?autore:

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.

Dati bibliografici

Titolo: Bandit Algorithms for Website Optimization: ...
Casa editrice: O'Reilly Media
Data di pubblicazione: 2013
Legatura: Paperback
Condizione: Very Good
Condizione sovraccoperta: No Jacket