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GitHub / py-why / EconML

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/py-why%2FEconML

Stars: 3,545
Forks: 675
Open Issues: 343

License: other
Language: Jupyter Notebook
Repo Size: 43.1 MB
Dependencies: 0

Created: about 6 years ago
Updated: 18 days ago
Last pushed: 24 days ago
Last synced: 21 days ago

Commit Stats

Commits: 429
Authors: 39
Mean commits per author: 11.0
Development Distribution Score: 0.431
More commit stats: https://commits.ecosyste.ms/hosts/GitHub/repositories/py-why/EconML

Topics: causal-inference, causality, econometrics, economics, machine-learning, treatment-effects

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