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