Machine Learning
Machine Learning
intermediate
Recommender Systems from Scratch
Build a recommender end to end: implicit-feedback matrix factorisation, content-based retrieval with embeddings, two-stage retrieve-then-rank architectures, and the cold-start problem every real system faces. Evaluated with offline ranking metrics and an honest discussion of why they disagree with A/B tests.
HT
Hiroshi Tanaka
4.9
$89.00
15 hours