Fine-Grained NLP with Embeddings: Retrieval, Classification, and Clustering

Production NLP systems use embeddings differently depending on the task. Semantic search, document classification, topic clustering, and duplicate detection each require distinct embedding strategies, model choices, and similarity metrics. Getting these details right is what separates demos from deployed systems.