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.
Why this job: works in the areas we cover, but does not say which job it does
What it does
For detailed information about the package, consult the documentation at https://www.pywhy.org/EconML/.
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Active
- Last commit 9 days ago
- Stars
- 4,850
- +8 this week
- Licence
- Custom
- Read before business use
- Downloads for
- None listed
- No release files
- Latest version
- v0.17.0
- Released 3 months ago
- Built with
- Jupyter Notebook
- 81% of the code
Is it looked after?
- Contributors
- Not stated
- Last 90 days
- Issues
- 39% closed
- 382 still open
- Pull requests
- 336 merged
- 46 waiting
- Releases
- 35
- 1 in the last year
- No contributing guide
- Security policy (opens in new tab)
- No code of conduct
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More: languages, topics, project record and preview image
Languages
- Jupyter Notebook 81%
- Python 17%
- Cython 1%
- TeX <1%
Topics
- machine-learning
- economics
- causal-inference
- causality
- econometrics
- treatment-effects
Project record
- JobOther AI tools
- StatusListed
- Commits593
- Forks834
- Watching85
- Stars in 28 days+43
- CreatedApr 30, 2018
- First seen by usNov 7, 2026
- CheckedNov 10, 2026
