Chapter 5. Taking recommenders to production
This chapter covers
- Analyzing data from a real dating site
- Designing and refining a recommender engine solution
- Deploying a web-based recommender service in production
So far, this book has toured the recommender algorithms and variants that Apache Mahout provides, and discussed how to evaluate the accuracy and performance of a recommender. The next step is to apply all of this to a real data set to create an effective recommender engine from scratch based on data. You’ll create one based on data taken from a dating site, and then you’ll turn it into a deployable, production-ready web service.
There’s no one standard approach to building a recommender for given data and a given problem domain. ...
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