py-why/dowhy

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

Pythondata-sciencemachine-learningpython3graphical-modelscausalitybayesian-networkscausal-inferencetreatment-effectscausal-modelsdo-calculuscausal-machine-learning
This is stars and forks stats for /py-why/dowhy repository. As of 06 May, 2024 this repository has 6210 stars and 867 forks.

Introducing DoWhy and the 4 steps of causal inference | Microsoft Research Blog | Video Tutorial | Arxiv Paper | Arxiv Paper (GCM-extension) | Slides Read the docs | Try it online! Case Studies using DoWhy: Hotel booking cancellations | Effect of customer loyalty programs | Optimizing article headlines | Effect of home visits on infant health (IHDP) | Causes of customer churn/attrition As computing systems are more frequently and more actively intervening in societally critical domains such as healthcare,...
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