Documentation

Sponsor

Tip

You can support this project in various ways ❤️

• Star this repo at the github page.

• Become a Sponsor!

• Buy me a coffee! I ❤️ coffee :)

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• You can also buy a digital educational product over here.

• Contribute in the form of feature requests, idea discussions, reporting bugs, opening pull requests.

Cheers Mate.

Medium Blog Posts

Note

• Guide in Detecting Causal Relationships using Bayesian Structure Learning in Python

• Guide in Designing Knowledge-Driven Models using Bayesian Theorem

• A Comparative Analysis of Libraries to Reveal Hidden Causality in Your Dataset

GitHub Repository

Note

Source code of bnlearn can be found at GitHub

Google Colab Notebooks

Note

• General Functionalities

• Inferences on the Salary Dataset

• Knowledge-Driven Approach

Citing bnlearn

The BibTeX citation can be found in the right side menu at the GitHub page.

References

• Probabilistic Graphical Models using pgmpy

• Causality, Pearl, 2009, 2nd Edition

• If Correlation Doesn’t Imply Causation, Then What Does? by Michael Nielsen

• Lecture Notes from Jonas Peters

• Elements of Causal Inference

• Causality Slides

Related Packages

• Causal Graphical Models

• Causality

• Causal Inference

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