| Description: | This package contains the highly optimized version of word2vec from
gensim. It is highly recommend to use this. If you don't need
the highly optimized version of word2vec, it is sufficient to install
the "python-gensim-core"-package.
Gensim is a Python library for topic modelling, document indexing
and similarity retrieval with large corpora. Target audience is
the natural language processing (NLP) and information retrieval
(IR) community.
Features:
* All algorithms are memory-independent w.r.t. the corpus size
(can process input larger than RAM).
* Intuitive interfaces
- easy to plug in your own input corpus/datastream (trivial
streaming API)
- easy to extend with other Vector Space algorithms (trivial
transformation API)
* Efficient implementations of popular algorithms, such as online
Latent Semantic Analysis (LSA/LSI), Latent Dirichlet Allocation (LDA),
Random Projections (RP), Hierarchical Dirichlet Process (HDP) or
word2vec deep learning.
* Distributed computing: can run Latent Semantic Analysis and Latent
Dirichlet Allocation on a cluster of computers, and word2vec on
multiple cores.
* Extensive HTML documentation and tutorials. |
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