In machine learning, an embedding is a learned representation of an object, such as a word, sentence, or image, as a vector of real numbers. This representation is designed to capture the semantic meaning of the object, so that similar objects are represented by similar vectors.
A core concept in natural language processing and deep learning.
The foundation of modern search engines, recommender systems, and large language models.