//- 💫 DOCS > USAGE > WORD VECTORS & SIMILARITIES

include ../_includes/_mixins

+section("basics")
    +aside("Training word vectors")
        |  Dense, real valued vectors representing distributional similarity
        |  information are now a cornerstone of practical NLP. The most common way
        |  to train these vectors is the #[+a("https://en.wikipedia.org/wiki/Word2vec") word2vec]
        |  family of algorithms. If you need to train a word2vec model, we recommend
        |  the implementation in the Python library
        |  #[+a("https://radimrehurek.com/gensim/") Gensim].

    include _spacy-101/_similarity
    include _spacy-101/_word-vectors

+section("custom")
    +h(2, "custom") Customising word vectors
    include _vectors-similarity/_custom

+section("gpu")
    +h(2, "gpu") Storing vectors on a GPU
    include _vectors-similarity/_gpu