subtopic

Embeddings and cosine similarity

Learn that a sentence-embedding model (a small BERT-like encoder) turns a whole sentence into one vector (e.g. 384 numbers) so that sentences with the same meaning are close, even with different words. Similarity = cosine similarity between vectors. This is the contextual upgrade of the word vectors from Module 1.

Builds on: 1.3 Turning text into numbers