Gensim, programmed by Radim Řehůřek, is an open source package that is suitable for the analysis of large textual collections with the help of parallel distributable online algorithms. Among advanced functionalities, it implements Latent Semantic Analysis (LSA), topic modeling by Latent Dirichlet Allocation (LDA), and Google's word2vec, a powerful algorithm that transforms text into vector features that can be used in supervised and unsupervised machine learning:
- Website: http://radimrehurek.com/gensim/
- Version at the time of print: 3.4.0
- Suggested install command: pip install gensim
