Gensim is an open-source library for unsupervised topic modeling and natural language processing, using modern statistical machine learning. Gensim is implemented in Python and Cython for performance.
Core advantages (features)
Gensim includes streamed parallelized implementations of fastText, word2vec and doc2vec algorithms, as well as latent semantic analysis (LSA, LSI, SVD), non-negative matrix factorization (NMF), latent Dirichlet allocation (LDA), tf-idf and random projections.
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