Bandit Algorithms for Website Optimization
Developing, Deploying, and Debugging
Publisher: O'Reilly Media
Released: December 2012
Pages: 88

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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oreillyBandit Algorithms for Website Optimization
 
4.0

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      5.0

      Great introduction!

      By Paul

      from Brooktondale, NY

      About Me Developer

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      Pros

      • Accurate
      • Concise
      • Easy to understand
      • Helpful examples
      • Well-written

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        • Intermediate

        Comments about oreilly Bandit Algorithms for Website Optimization:

        The multi-armed bandit is a modern addition to decision theory that addresses the question of balancing learning vs. maximizing short term profit.

        This book explains the topic in a modern manner, based on simple implementations and a testing and simulation framework written in Python.

        This book is much more accessible than academic treatments of the multi-arm bandit and will quickly get you to understand what you can do with these algorithms and how to implement them.

         
        3.0

        Interesting, wish it was more technical

        By Andrew S.

        from Madison, WI

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        Pros

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        • Well-written

        Cons

        • Not comprehensive enough

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        Comments about oreilly Bandit Algorithms for Website Optimization:

        The book was good, I'm glad they went over different methods for handling the algorithms. I was left feeling that I didn't understand how to actually apply this in my real websites. Here's an example, most people will have a website that shows things on the homepage. It's a success if they visit the sales page and a failure if they don't. When we show them the homepage is there a method to consider it a failure until it succeeds? I didn't see any information for having a delayed success.

        (4 of 4 customers found this review helpful)

         
        4.0

        Bridges the theoretical and practical

        By XYZ

        from Cambridge, MA

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        Pros

        • Concise
        • Easy to understand
        • Good Value
        • Well-written

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          • Intermediate

          Comments about oreilly Bandit Algorithms for Website Optimization:

          (Disclosure: I received a free review copy of this book.)

          Don't let the small size of this book fool you: even though you could easily read it in an afternoon, it'll change your thinking about split testing in ways that could pay off big.

          In under 80 pages White sketches out three alternatives to traditional A/B testing, a method for testing them, some considerations for the working programmer who has to write code for the real world, and some general principles for further explanation.

          The choice of Python for code examples was also inspired. I know plenty of languages but Python isn't one of them; nevertheless, I was able to follow along without trouble.

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