Overview of Recommender Algorithms – Part 5

This is the final part in a five part series on overviewing recommender algorithms. In the first post, we introduced the main types of recommender algorithms by providing a cheatsheet for them. In the second, we covered the different types of collaborative filtering algorithms highlighting some of their nuances and how they differ from one… Read More Overview of Recommender Algorithms – Part 5

Overview of Recommender Algorithms – Part 3

This is the third in a multi-part post. In the first post, we introduced the main types of recommender algorithms by providing a cheatsheet for them. In the second post, covered the different types of collaborative filtering algorithms highlighting some of their nuances and how they differ from one another. In this blog post, we’ll… Read More Overview of Recommender Algorithms – Part 3

Evaluations

In building a recommender, it’s common to ask the question, how well does it work?  Ultimately, you’ll only know when you release it live to users and measure it against your targets such as increasing sales or user activity.  It’s unlikely, however, that you’ll get it right first time round and you’ll want to be… Read More Evaluations

The Components of a Recommender System

A recommender system is made up of five core components (Figure 1). This post is intended to give the big picture. In future posts we’ll jump into details. Arguably, the core component is the one that generates recommendations for users; the recommender model (2).  It is responsible for taking data, such as user preferences and descriptions… Read More The Components of a Recommender System