Natural Language Processing

spaCy – industrial strength natural language processing

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).

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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