Word2Vec — a baby step in Deep Learning but a giant leap towards Natural Language Processing

Word2Vec model is used for learning vector representations of words called “word embeddings”. This is typically done as a preprocessing step, after which the learned vectors are fed into a discriminative model (typically an RNN) to generate predictions and perform all sort of interesting things.