# pgmpy/pgmpy

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3,277 stars · 1,127 forks · Python · MIT

## Links

- GitHub: https://github.com/pgmpy/pgmpy
- Homepage: https://pgmpy.org/
- awesome-repositories: https://awesome-repositories.com/repository/pgmpy-pgmpy.md

## Topics

`bayesian-networks` `causal-discovery` `causal-effect` `causal-identification` `causal-inference` `causal-models` `causal-prediction` `causal-validation` `graphical-models` `hacktoberfest` `mixed-data` `probabilistic-inference` `python` `simulation` `synthetic-data`

## Description

Python Toolkit for Causal and Probabilistic Reasoning

## Tags

### Part of an Awesome List

- [General Machine Learning](https://awesome-repositories.com/f/awesome-lists/ai/general-machine-learning.md) — Library for probabilistic graphical models.
- [Machine Learning](https://awesome-repositories.com/f/awesome-lists/ai/machine-learning.md) — A Python library for probabilistic graphical models and Bayesian networks.
- [Probabilistic Modeling](https://awesome-repositories.com/f/awesome-lists/ai/probabilistic-modeling.md) — Library for working with Probabilistic Graphical Models.
- [Statistical Modeling](https://awesome-repositories.com/f/awesome-lists/devtools/statistical-modeling.md) — Probabilistic and causal inference using graphical models.