Gensim

Gensim

Radim Řehůřek
word2vec

word2vec

Google

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

IronPython is an open-source implementation of the Python programming language which is tightly integrated with .NET. IronPython can use .NET and Python libraries, and other .NET languages can use Python code just as easily. Experience a more interactive .NET and Python development experience with Python Tools for Visual Studio. IronPython is an excellent addition to .NET, providing Python developers with the power of the .NET. Existing .NET developers can also use IronPython as a fast and expressive scripting language for embedding, testing, or writing a new application from scratch. The CLR is a great platform for creating programming languages, and the DLR makes it all the better for dynamic languages. Also, the .NET (base class library, presentation foundation, etc.) gives developers an amazing amount of functionality and power. IronPython uses Python syntax and standard libraries and so your Python code will need to be updated accordingly.

About

Wing Python IDE was designed from the ground up for Python, to bring you a more productive development experience. Type less and let Wing worry about the details. Get immediate feedback by writing your Python code interactively in the live runtime. Easily navigate code and documentation. Avoid common errors and find problems early with assistance from Wing's deep Python code analysis. Keep code clean with smart refactoring and code quality inspection. Debug any Python code. Inspect debug data and try out bug fixes interactively without restarting your app. Work locally or on a remote host, VM, or container. Wingware's 21 years of Python IDE experience bring you a more Pythonic development environment. Wing was designed from the ground up for Python, written in Python, and is extensible with Python. So you can be more productive.

About

Word2Vec is a neural network-based technique for learning word embeddings, developed by researchers at Google. It transforms words into continuous vector representations in a multi-dimensional space, capturing semantic relationships based on context. Word2Vec uses two main architectures: Skip-gram, which predicts surrounding words given a target word, and Continuous Bag-of-Words (CBOW), which predicts a target word based on surrounding words. By training on large text corpora, Word2Vec generates word embeddings where similar words are positioned closely, enabling tasks like semantic similarity, analogy solving, and text clustering. The model was influential in advancing NLP by introducing efficient training techniques such as hierarchical softmax and negative sampling. Though newer embedding models like BERT and Transformer-based methods have surpassed it in complexity and performance, Word2Vec remains a foundational method in natural language processing and machine learning research.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

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

Audience

Developers requiring a scripting language for embedding, testing, or writing new applications

Audience

Python developers seeking a tool to build applications

Audience

Researchers, data scientists, and developers working in natural language processing (NLP) and machine learning who need efficient word embeddings for text analysis and semantic understanding

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

API

Offers API

API

Offers API

Screenshots and Videos

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Pricing

Free
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

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

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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 3.0 / 5
ease 5.0 / 5
features 5.0 / 5
design 1.0 / 5
support 4.0 / 5

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:

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Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

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

Company Information

IronPython
ironpython.net

Company Information

Wingware
Founded: 1999
United States
wingware.com

Company Information

Google
Founded: 1998
United States
code.google.com/archive/p/word2vec/

Alternatives

GloVe

GloVe

Stanford NLP

Alternatives

Alternatives

Alternatives

word2vec

word2vec

Google
Gensim

Gensim

Radim Řehůřek
GloVe

GloVe

Stanford NLP
Cohere

Cohere

Cohere AI
Mojo

Mojo

Modular
LexVec

LexVec

Alexandre Salle

Categories

Categories

Categories

Categories

Application Development Features

Access Controls/Permissions
Code Assistance
Code Refactoring
Collaboration Tools
Compatibility Testing
Data Modeling
Debugging
Deployment Management
Graphical User Interface
Mobile Development
No-Code
Reporting/Analytics
Software Development
Source Control
Testing Management
Version Control
Web App Development

Integrations

Amazon Web Services (AWS)
Apache Subversion
C
C++
Cython
Django
Docker
Eclipse IDE
Emacs
Gensim
Git
Google App Engine
MATLAB
NumPy
Vagrant
Visual Studio
Wing
Xcode
fastText
word2vec

Integrations

Amazon Web Services (AWS)
Apache Subversion
C
C++
Cython
Django
Docker
Eclipse IDE
Emacs
Gensim
Git
Google App Engine
MATLAB
NumPy
Vagrant
Visual Studio
Wing
Xcode
fastText
word2vec

Integrations

Amazon Web Services (AWS)
Apache Subversion
C
C++
Cython
Django
Docker
Eclipse IDE
Emacs
Gensim
Git
Google App Engine
MATLAB
NumPy
Vagrant
Visual Studio
Wing
Xcode
fastText
word2vec

Integrations

Amazon Web Services (AWS)
Apache Subversion
C
C++
Cython
Django
Docker
Eclipse IDE
Emacs
Gensim
Git
Google App Engine
MATLAB
NumPy
Vagrant
Visual Studio
Wing
Xcode
fastText
word2vec
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