Embedding

Embedding, in the context of machine learning and natural language processing (NLP), refers to a technique used to represent items, such as words, entities, or even entire documents, in a continuous vector space. These vectors can capture semantic meanings and relationships between the items, allowing for effective analysis and processing. ### Key Points about Embeddings: 1. **Dense Representation**: Unlike traditional representations (e.g., one-hot encoding), embeddings provide a more compact and informative representation.