Building memory-efficient meta-hybrid recommender engine: back to front (part 2)

Building Memory-Efficient Meta-Hybrid Recommender Engine: Back to Front (part 2)

Series overview

In the previous part, we reviewed the mechanics of a memory-based recommender system and built a custom collaborative filtering recommender. Today we will apply “out-of-box” recommenders from popular Python modules, evaluate their efficiency, and try some techniques to seamlessly improve the SVD prediction algorithm known as the Netflix prize winner. At RBC Group we are open to sharing our experience in designing so-called …

building clustering hybrid machine learning memory meta movies part recommender systems tfidf-vectorizer