One of my internet-friends created something very nice. Dr. Bunsen is a data wrangler in the real world and he put his skills together to create a beer recommendation service called BeerAI. You can read about the project on his website
To make beer recommendations, BeerAI uses several low rank approximation techniques in conjunction with collaborative filtering and nearest neighbor methods. The latent factor models capture hidden features of the data that haven’t been explicitly modeled, thereby providing some of the novelty in the recommendations. By combining all of these approaches, ensemble learning helps to improve the recommendations that the system produces and eliminate bad recommendations resulting from user biases, algorithmic pitfalls, or sparsity issues.
So, um, yeah. Beer good.
What I really appreciate is that if you do a search based on a local brewery BeerAI will understand that you probably don’t want recommendations from small breweries 1000’s of miles away.