Audience

Developers requiring a solution to build products, custom components and workflows while gathering insights

About spaCy

spaCy is designed to help you do real work, build real products, or gather real insights. The library respects your time and tries to avoid wasting it. It's easy to install, and its API is simple and productive. spaCy excels at large-scale information extraction tasks. It's written from the ground up in carefully memory-managed Cython. If your application needs to process entire web dumps, spaCy is the library you want to be using. Since its release in 2015, spaCy has become an industry standard with a huge ecosystem. Choose from a variety of plugins, integrate with your machine learning stack, and build custom components and workflows. Components for named entity recognition, part-of-speech tagging, dependency parsing, sentence segmentation, text classification, lemmatization, morphological analysis, entity linking, and more. Easily extensible with custom components and attributes. Easy model packaging, deployment, and workflow management.

Pricing

Starting Price:
Free
Pricing Details:
Open source
Free Trial:
Free Trial available.

Integrations

API:
Yes, spaCy offers API access

Ratings/Reviews

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Company Information

spaCy
Founded: 2015
United States
spacy.io

Videos and Screen Captures

spaCy Screenshot 1
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Product Details

Platforms Supported
Cloud
Training
Documentation
Videos
Support
Online

spaCy Frequently Asked Questions

Q: What kinds of users and organization types does spaCy work with?
Q: What languages does spaCy support in their product?
Q: What other applications or services does spaCy integrate with?
Q: Does spaCy have an API?
Q: What type of training does spaCy provide?
Q: Does spaCy offer a free trial?
Q: How much does spaCy cost?

spaCy Product Features

Natural Language Processing

Sentence Segmentation
Tokenization
Stemming/Lemmatization
Part-of-Speech Tagging
Parsing
Named Entity Recognition
Co-Reference Resolution
In-Database Text Analytics
Open Source Integrations
Natural Language Generation (NLG)

Text Mining

Summarization
Language Detection
Boolean Queries
Taxonomy Classification
Document Filtering
Sentiment Analysis
Graphical Data Presentation
Predictive Modeling
Topic Clustering
Text Analysis
Tagging