Machine Learning: Make Your Own Recommender System

4

 

 

 

WORKING WITH DATA

 

Data for a typical recommender system consists of two entities in the form of “users” and “items” organized in what’s called a utility matrix. While it sounds intimidating, a utility matrix is a simple pivot table containing pairs of values, such as an individual user and their ratings for given items.

 

Table 2: Example of a utility matrix

 

Users are often arranged vertically in rows, and items are placed horizontally in columns. The preferences of each user for a given item can be found by searching for the relevant column. The aligning cell depicts the user’s preference for that item, which is generally represented ...