word2vec

word2vec

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About

CVXOPT is a free software package for convex optimization based on the Python programming language. It can be used with the interactive Python interpreter, on the command line by executing Python scripts, or integrated in other software via Python extension modules. Its main purpose is to make the development of software for convex optimization applications straightforward by building on Python’s extensive standard library and on the strengths of Python as a high-level programming language. Efficient Python classes for dense and sparse matrices (real and complex), with Python indexing and slicing and overloaded operations for matrix arithmetic. Interfaces to the linear programming solver in GLPK, the semidefinite programming solver in DSDP5, and the linear, quadratic and second-order cone programming solvers in MOSEK.

About

The core of extensible programming is defining functions. Python allows mandatory and optional arguments, keyword arguments, and even arbitrary argument lists. Whether you're new to programming or an experienced developer, it's easy to learn and use Python. Python can be easy to pick up whether you're a first-time programmer or you're experienced with other languages. The following pages are a useful first step to get on your way to writing programs with Python! The community hosts conferences and meetups to collaborate on code, and much more. Python's documentation will help you along the way, and the mailing lists will keep you in touch. The Python Package Index (PyPI) hosts thousands of third-party modules for Python. Both Python's standard library and the community-contributed modules allow for endless possibilities.

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

Audience

Component Library solution for developers

Audience

Developers interested in a beautiful but advanced programming language

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

API

Offers API

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Screenshots and Videos

No images available

Pricing

Free
Free Version
Free Trial

Pricing

Free
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 5.0 / 5
ease 5.0 / 5
features 5.0 / 5
design 5.0 / 5
support 5.0 / 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:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

CVXOPT
cvxopt.org

Company Information

Python
Founded: 1991
www.python.org

Company Information

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

Alternatives

Alternatives

Alternatives

Solver SDK

Solver SDK

Frontline Systems
Gensim

Gensim

Radim Řehůřek
GloVe

GloVe

Stanford NLP
LexVec

LexVec

Alexandre Salle

Categories

Categories

Categories

Integrations

AI Crypto-Kit
AWS Thinkbox Deadline
Alumnium
Bluefish
Browser Use
DeepSeek-V3
Gable
GaiaNet
GitLab Duo
LiteRT
Luminal
Luminary Cloud
Nextdata
Outspeed
Qoder
Speakeasy
Superblocks
dstack
iSports API
python-sql

Integrations

AI Crypto-Kit
AWS Thinkbox Deadline
Alumnium
Bluefish
Browser Use
DeepSeek-V3
Gable
GaiaNet
GitLab Duo
LiteRT
Luminal
Luminary Cloud
Nextdata
Outspeed
Qoder
Speakeasy
Superblocks
dstack
iSports API
python-sql

Integrations

AI Crypto-Kit
AWS Thinkbox Deadline
Alumnium
Bluefish
Browser Use
DeepSeek-V3
Gable
GaiaNet
GitLab Duo
LiteRT
Luminal
Luminary Cloud
Nextdata
Outspeed
Qoder
Speakeasy
Superblocks
dstack
iSports API
python-sql
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