Language & LLMs

What Is word2vec?

word2vec is a family of models that learn word embeddings by training a shallow neural network to predict a word from its neighbors or its neighbors from the word. Its two main architectures are continuous bag-of-words (CBOW) and skip-gram. The resulting vectors capture semantic relationships, such as analogies between related words.