AI engineering glossary · NLP embeddings
What is text embedding model?
Text embedding model (also called Embedding model): A trained model that converts text of any length into a fixed-size vector so that texts with similar meaning are close together. It is used for search, clustering, recommendation and retrieval, and is typically available through a library or hosted service.
Text embedding model: an example
A model turns each of 10,000 support tickets into a 768-number vector, and near vectors group similar complaints.
Related terms
More NLP embeddings terms
Where you learn it
Text embedding model is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.