**Latent Dirichlet Allocation (LDA)**, **Random Projections (RP)**, **Hierarchical Dirichlet Process (HDP)** or **word2vec deep learning**. * Efficient multicore implementations of popular algorithms, such as online **Latent Semantic Analysis (LSA/LSI/SVD)**, * easy to extend with other Vector Space algorithms (simple transformation API) * easy to plug in your own input corpus/datastream (simple streaming API) the corpus size (can process input larger than RAM, streamed, out-of-core)
* All algorithms are **memory-independent** w.r.t. Target audience is the *natural language processing* (NLP) and *information retrieval* (IR) community.
Gensim is a Python library for *topic modelling*, *document indexing* and *similarity retrieval* with large corpora.
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