Gensim

Gensim

Radim Řehůřek
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About

Gensim is a free, open source Python library designed for unsupervised topic modeling and natural language processing, focusing on large-scale semantic modeling. It enables the training of models like Word2Vec, FastText, Latent Semantic Analysis (LSA), and Latent Dirichlet Allocation (LDA), facilitating the representation of documents as semantic vectors and the discovery of semantically related documents. Gensim is optimized for performance with highly efficient implementations in Python and Cython, allowing it to process arbitrarily large corpora using data streaming and incremental algorithms without loading the entire dataset into RAM. It is platform-independent, running on Linux, Windows, and macOS, and is licensed under the GNU LGPL, promoting both personal and commercial use. The library is widely adopted, with thousands of companies utilizing it daily, over 2,600 academic citations, and more than 1 million downloads per week.

About

Scikit-learn provides simple and efficient tools for predictive data analysis. Scikit-learn is a robust, open source machine learning library for the Python programming language, designed to provide simple and efficient tools for data analysis and modeling. Built on the foundations of popular scientific libraries like NumPy, SciPy, and Matplotlib, scikit-learn offers a wide range of supervised and unsupervised learning algorithms, making it an essential toolkit for data scientists, machine learning engineers, and researchers. The library is organized into a consistent and flexible framework, where various components can be combined and customized to suit specific needs. This modularity makes it easy for users to build complex pipelines, automate repetitive tasks, and integrate scikit-learn into larger machine-learning workflows. Additionally, the library’s emphasis on interoperability ensures that it works seamlessly with other Python libraries, facilitating smooth data processing.

Platforms Supported

Windows Supported
Mac Supported
Linux Supported
Cloud Not Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Supported
Mac Supported
Linux Supported
Cloud Not Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

Machine learning practitioners seeking a solution for topic modeling and semantic analysis of large text corpora

Audience

Engineers and data scientists requiring a solution to manage and improve their machine learning research

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version Supported
Free Trial Not Supported

Pricing

Free
Free Version Supported
Free Trial Not Supported

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

Radim Řehůřek
Founded: 2009
Czech Republic
radimrehurek.com/gensim/

Company Information

scikit-learn
United States
scikit-learn.org/stable/

Alternatives

GloVe

GloVe

Stanford NLP

Alternatives

Gensim

Gensim

Radim Řehůřek
word2vec

word2vec

Google
ML.NET

ML.NET

Microsoft
MLlib

MLlib

Apache Software Foundation
Cohere

Cohere

Cohere AI
Keepsake

Keepsake

Replicate

Categories

Categories

Machine Learning Supported

Integrations

NumPy Supported
Python Supported
C Supported
Cython Supported
DagsHub Not Supported
Databricks Not Supported
Flower Not Supported
GLM-5.1 Not Supported
GLM-5.2 Not Supported
GLM-5.3 Not Supported
Guild AI Not Supported
Keepsake Not Supported
MLJAR Studio Not Supported
Matplotlib Not Supported
ModelOp Not Supported
Thunder Compute Not Supported
Train in Data Not Supported
fastText Supported
word2vec Supported

Integrations

NumPy Supported
Python Supported
C Not Supported
Cython Not Supported
DagsHub Supported
Databricks Supported
Flower Supported
GLM-5.1 Supported
GLM-5.2 Supported
GLM-5.3 Supported
Guild AI Supported
Keepsake Supported
MLJAR Studio Supported
Matplotlib Supported
ModelOp Supported
Thunder Compute Supported
Train in Data Supported
fastText Not Supported
word2vec Not Supported
Claim Gensim and update features and information
Claim Gensim and update features and information
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Claim scikit-learn and update features and information