"GloVe"

GloVe (Global Vectors for Word Representation) is a technique used in natural language processing to create meaningful word embeddings—numerical representations of words. It analyzes large text datasets to understand how often words appear together and captures the relationships between them. For example, it recognizes that "king" and "queen" are related and that the difference between "king" and "queen" is similar to "man" and "woman." These embeddings help computers understand language context, making tasks like translation, search, or sentiment analysis more accurate by representing words in a way that reflects their meanings and relationships.