causal-prediction

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All3 Jupyter Notebook2 Python1

pgmpy /pgmpy

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Python library for causal inference and probabilistic modeling.

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

UpdatedOct 29, 2025
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pgmpy /pgmpy_tutorials

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Tutorials on Causal Inference and pgmpy

python-notebooks causal-inference pgmpy causal-discovery causal-graphs causal-identification causal-prediction

UpdatedAug 7, 2025
Jupyter Notebook

Mechanism-learn is a simple method to deconfound observational data such that any appropriate machine learning model is forced to learn predictive relationships between effects and their causes, despite the potential presence of multiple unknown and unmeasured confounding. The library is compatible with most existing ML deployments.

causal-inference causal-machine-learning causal-prediction

UpdatedOct 9, 2025
Jupyter Notebook

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