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.
MIT license (see the file LICENSE.txt).
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.