CausalML: Python Package for Causal Machine Learning

TL;DR

CausalML is a Python package that provides implementations of causal inference algorithms integrated with machine learning, aiming to bridge theoretical research and practical application.

Contribution

This paper introduces a Python package that consolidates causal inference and machine learning algorithms for accessible practical use.

Findings

Provides a comprehensive collection of causal inference algorithms in Python

Facilitates practical application of causal ML methods

Bridges gap between theory and practice in causal inference

Abstract

CausalML is a Python implementation of algorithms related to causal inference and machine learning. Algorithms combining causal inference and machine learning have been a trending topic in recent years. This package tries to bridge the gap between theoretical work on methodology and practical applications by making a collection of methods in this field available in Python. This paper introduces the key concepts, scope, and use cases of this package.