An embedding is a numerical representation of data, such as text, images, audio, or video, in a vector space. Embeddings are designed to capture meaningful relationships so that similar items are positioned near each other and can be used for search, clustering, classification, or retrieval.
A numerical representation of data, such as text, images, or videos, that captures relationships between different inputs. Embeddings are generated during the training phase of a model by converting text, image, and video into arrays of floating point numbers that are called vectors. Embeddings often reduce the dimensionality of data, which helps to enhance computational efficiency and to enable the processing of large datasets.