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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

Apache Ossie serves as an open specification and conversion toolkit designed for the seamless exchange of semantic metadata among analytics, business intelligence, and AI systems. Utilizing a YAML-based format, it articulates semantic models, datasets, fields, metrics, dimensions, relationships, and SQL expressions in a manner that is easily transferable. This enables data and analytics engineers to create, translate, and repurpose these definitions across interconnected platforms, thus ensuring a unified business context for reporting and AI-driven analysis. As a collaborative initiative, the project operates under the Apache License 2.0, and the availability of conversions is contingent upon the specific implementation by each platform. Additionally, this initiative fosters collaboration and innovation within the open-source community, encouraging contributions that enhance the toolkit's capabilities.

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.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

No images available

Screenshots View All

Integrations

C No 
Cube Yes 
Cython No 
Databricks Yes 
Hex Yes 
Holistics Yes 
NumPy No 
Omni Yes 
Python No 
Salesforce Yes 
Sigma Yes 
Snowflake Yes 
Tableau Yes 
ThoughtSpot Yes 
WisdomAI Yes 
dbt Yes 
fastText No 
word2vec No 

Integrations

C Yes 
Cube No 
Cython Yes 
Databricks No 
Hex No 
Holistics No 
NumPy Yes 
Omni No 
Python Yes 
Salesforce No 
Sigma No 
Snowflake No 
Tableau No 
ThoughtSpot No 
WisdomAI No 
dbt No 
fastText Yes 
word2vec Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version Yes 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Apache Software Foundation

Founded

1999

Country

United States

Website

ossie.apache.org

Vendor Details

Company Name

Radim Řehůřek

Founded

2009

Country

Czech Republic

Website

radimrehurek.com/gensim/

Product Features

Product Features

Natural Language Processing

Co-Reference Resolution No 
In-Database Text Analytics No 
Named Entity Recognition No 
Natural Language Generation (NLG) No 
Open Source Integrations No 
Parsing No 
Part-of-Speech Tagging No 
Sentence Segmentation No 
Stemming/Lemmatization No 
Tokenization No 

Alternatives

No Alternatives

Alternatives

word2vec Reviews

word2vec

Google
GloVe Reviews

GloVe

Stanford NLP