The Illustrated Word2vec

This is a word embedding for the word “king” (GloVe vector trained on Wikipedia):

It’s a list of 50 numbers. The most famous example is the formula: “king” – “man” + “woman”:

We can visualize this analogy as we did previously:

The resulting vector from “king-man+woman” doesn’t exactly equal “queen”, but “queen” is the closest word to it from the 400,000 word embeddings we have in this collection. But before we get to word2vec, we need to look at a conceptual parent of word embeddings: the neural language model.

Source: jalammar.github.io