Description
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: John Myles White
Publisher: O'Reilly Media
Published: 01/03/2013
Pages: 88
Binding Type: Paperback
Weight: 0.35lbs
Size: 9.07h x 6.99w x 0.23d
ISBN13: 9781449341336
ISBN10: 1449341330
BISAC Categories:
- Computers | Programming | Algorithms
- Computers | Languages | Python
- Computers | Internet | General
About the Author
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.