Word2Vec is a popular natural language processing technique that is used to create high-quality vector representations of words from large datasets of text. It is a neural network based model that is capable of capturing the semantic and syntactic meaning of words, and it has been widely used in various downstream NLP tasks such as text classification, sentiment analysis, and machine translation.
