Finding similar users
Collaborative filtering is built around the premise that users who have ranked items similarly in the past have similar tastes, and therefore are likely to rate new items in a similar fashion.
A subset of the movies dataset has been loaded as user_ratings_subset
.
The DataFrame contains user ratings with a row for each user and a column for each movie.
Examine user_ratings_subset
. Which user is most similar to User A?
This exercise is part of the course
Building Recommendation Engines in Python
Hands-on interactive exercise
Turn theory into action with one of our interactive exercises
