Appendix: Causal AI Tools and Libraries

This appendix is a supplement to Chapter 7. It is not an exhaustive list of every causal AI tool and library that you might encounter, but it is our attempt to help readers understand the types of tools that are emerging. The following table summarizes more than 30 popular tools, most of which are open source. The sites for these tools are found easily via a web search.

Tool Category Description URL
Azua Causal Inference Library Azua is a project focused on observational decision-making approaches and processes in causal inference and counterfactual analysis. It was separated from the Causica project to specifically address observational decision-making. https://github.com/microsoft/project-azua
CausalInference Causal Inference Library Causal Inference in Python (Causalinference) is an open-source project that implements various statistical and econometric methods used in the field of causal inference. It includes features for assessing overlap in covariate distributions, estimating propensity scores, and estimating treatment effects through matching, weighting, and least squares. https://causalinferenceinpython.org
CausalML Causal Inference Library CausalML is a Python-based tool created by a development team at Uber for uplift modeling and causal inference. It supports various approaches to estimate and validate the Conditional Average Treatment Effect (CATE) or Individual Treatment Effect (ITE) from experimental or observational ...

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