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A Python package for compiling and querying discrete probabilistic graphical models.

Project description

Compiled Knowledge

Compiled Knowledge is a Python package for compiling and querying discrete probabilistic graphical models. The aim of the project is:

  • to provide a Python library for compiling and querying probabilistic graphical models, specifically discrete factor graphs, which includes Bayesian networks
  • to be extremely efficient, flexible, and easy to use
  • to exhibit excellent design, code, and documentation
  • to support researchers and businesses wanting to explore and use probabilistic artificial intelligence.

License

MIT license (see the file LICENSE.txt).

More Information

Refer to the project online documentation at compiled-knowledge.readthedocs.io.

The primary repository for the project is github.com/ropeless/compiled_knowledge.

The Python package is available on PyPI, see pypi.org/project/compiled-knowledge.

For more information email info@compiledknowledge.org.

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compiled_knowledge-4.2.2.tar.gz (1.2 MB view details)

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