scientific-causal-ml

What problem does it solve?

Identify and estimate causal effects from observational data using machine learning-based causal inference methods to enable robust decision making.

Core Features & Use Cases

• DoWhy-based causal modeling for identifiability and estimation
• EconML-based Double ML, Causal Forest, and meta-learners for high-dimensional data
• Causal feature discovery and interpretation to reveal treatment effect heterogeneity

Quick Start

Provide a minimal example that identifies and estimates a causal effect using DoWhy on a dataset with treatment, outcome, and covariates.