Published on 20 February 2015 Tweet
We all love beers. And today, we face an unprecedented variety of options. We are overwhelmed by too many choices and couldn’t decide: What should I drink next?
In our Hack Reactor thesis project, I build a machine learning server using PredictionIO as a recommendation engine for beer. Boardly speaking, the app is based on the following two strategies:
The advantage of using matrix factorization is that it allows incorperation of additional information. When explicit feedback is not availabe (i.e. your ratings), we can infer user preferences using implicit feedback, such as your browsing history and search pattern.
As a result, OnTapp matches you with beers that suit your taste. To get a recommendation of beer and try our our demo, plesae visit: http://ontappapp.com/
Originally published at victorleungtw.com on January 20, 2015.