AI engineering glossary · Time series recsys
What is CF (collaborative filtering)?
Collaborative filtering (also called CF): A recommendation approach that predicts what a user will like from the behaviour of other users with similar tastes, without needing item descriptions. It works from patterns in a user-item interaction record.
Collaborative filtering: an example
Two users both liked films A, B and C; one also liked D, so D is suggested to the other.
Related terms
- User-based collaborative filtering
- Item-based collaborative filtering
- Matrix factorisation
- User-item matrix
More Time series recsys terms
- Content-based filtering
- Conversion rate
- Correlogram
- Counterfactual evaluation
- Croston's method
- Cyclical component
- DeepAR
- DeepFM
Where you learn it
Collaborative filtering is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.