spaCy is an open-source software library for advanced Natural Language Processing, written in the programming languages Python and Cython.
spaCy is designed to help you do real work — to build real products, or gather real insights.
spaCy comes with pre-trained statistical models and word vectors.
Features include:
- Models for spaCy can be installed as Python packages.
- Neural models for tagging, parsing and entity recognition.
- Non-destructive tokenization.
- Named entity recognition.
- “Alpha tokenization” support for over 31 languages.
- 13 Statistical models models for 8 languages.
- Pre-trained word vectors.
- Part-of-speech tagging.
- Labelled dependency parsing.
- Syntax-driven sentence segmentation.
- Text classification.
- Built in visualizers for syntax and NER.
- Convenient string-to-hash mapping.
- Export to numpy data arrays.
- Efficient binary serialization.
- Easy model packaging and deployment.
- State-of-the-art speed.
- Robust, rigorously evaluated accuracy.
- Deep learning integration. It interoperates seamlessly with TensorFlow, PyTorch, scikit-learn, Gensim and the rest of Python’s AI ecosystem.
- Comes with an extensive test suite.
- Cross-platform support – macOS / OS X, Linux, Windows (Cygwin, MinGW, Visual Studio).
Website: spacy.io
Support: GitHub code repository
Developer: Explosion AI and many contributors
License: MIT License
spaCy is written in Python. Learn Python with our recommended free books and free tutorials.
Return to Natural Language Processing | Return to Python Natural Language Tools
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