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Description
Gensim is an open-source Python library that specializes in unsupervised topic modeling and natural language processing, with an emphasis on extensive semantic modeling. It supports the development of various models, including Word2Vec, FastText, Latent Semantic Analysis (LSA), and Latent Dirichlet Allocation (LDA), which aids in converting documents into semantic vectors and in identifying documents that are semantically linked. With a strong focus on performance, Gensim features highly efficient implementations crafted in both Python and Cython, enabling it to handle extremely large corpora through the use of data streaming and incremental algorithms, which allows for processing without the need to load the entire dataset into memory. This library operates independently of the platform, functioning seamlessly on Linux, Windows, and macOS, and is distributed under the GNU LGPL license, making it accessible for both personal and commercial applications. Its popularity is evident, as it is employed by thousands of organizations on a daily basis, has received over 2,600 citations in academic works, and boasts more than 1 million downloads each week, showcasing its widespread impact and utility in the field. Researchers and developers alike have come to rely on Gensim for its robust features and ease of use.
Description
Semantic UI views words and classes as interchangeable elements. It employs a syntax derived from natural language, utilizing relationships like noun and modifier, as well as principles such as word order and plurality, to create intuitive connections between concepts. The framework incorporates straightforward phrases known as behaviors that activate various functionalities. Each decision made within a component is treated as a customizable setting, allowing developers to tailor their designs. Additionally, performance logging provides a means to identify bottlenecks without the need to sift through stack traces. With a user-friendly inheritance system and high-level theming variables, Semantic UI offers extensive freedom in design choices. Definitions extend beyond mere buttons on a webpage; the components of Semantic encompass various types of definitions, including elements, collections, views, modules, and behaviors, effectively addressing the full spectrum of interface design needs. This comprehensive approach ensures that developers can create rich, interactive user experiences.
API Access
Has API
API Access
Has API
Integrations
C
Cython
Dash
NumPy
Python
Semantic UI React
fastText
word2vec
Integrations
C
Cython
Dash
NumPy
Python
Semantic UI React
fastText
word2vec
Pricing Details
Free
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Radim Řehůřek
Founded
2009
Country
Czech Republic
Website
radimrehurek.com/gensim/
Vendor Details
Company Name
Semantic
Website
semantic-ui.com
Product Features
Natural Language Processing
Co-Reference Resolution
In-Database Text Analytics
Named Entity Recognition
Natural Language Generation (NLG)
Open Source Integrations
Parsing
Part-of-Speech Tagging
Sentence Segmentation
Stemming/Lemmatization
Tokenization
Product Features
Web Design
Autocompletion
Collaborative Editing
Content Management
Drag & Drop
Element Libraries
Programming Language Support
Syntax Highlighting
Templates