— · COMPUTER VISION
StyleNova
StyleNova fuses what an outfit looks like, what a shopper has liked before, and what similar shoppers bought into a single hybrid recommendation score. CLIP vision-language embeddings, TF-IDF content signals, and collaborative filtering feed the base model, while an online preference-learning loop keeps adjusting to each shopper in real time.
Stack
PythonPyTorchCLIPFastAPIscikit-learnNext.jsTypeScriptPrismaZustandFramer Motion
Highlights
- Hybrid scorer (CLIP ViT-B/32 + TF-IDF + collaborative filtering) reaches Precision@10 of 0.73
- Online preference learning improves recommendation relevance 32% after just 5 user interactions
- Cached CLIP embeddings deliver sub-200ms p95 API response for 10K+ concurrent users with zero cold-start