Francois Scharffe: Word embeddings as a service

PyData NYC 2015 This talk will show how to deal with word embeddings in python, from learning a model to using it in production in a django application. Word embeddings are a very convenient tool for performing a large variety of natural language processing task, like Part Of Speech tagging, Named Entity Recognition, or building similarity measures between documents. The Gensim library leverages the efficient word2vec algorithm with Cython optimizations allowing fast learning of word embedding models. Exp
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