Preference Based Recommendation Filtering

via “collaborative filtering and recommendation systems”

The in-person certificate courses are not free, but all of the content is available on Fast.ai as MOOCs.

Unique: Implements neural collaborative filtering with learned embeddings for both users and items, enabling non-linear interactions compared to traditional matrix factorization, and provides utilities for handling implicit feedback and cold-start scenarios

vs others: More accessible than building custom recommendation systems with PyTorch, but less feature-rich than dedicated recommendation frameworks (LightFM, Implicit) for production systems with complex business logic