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Facts
| Fact | 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. | microsoft/AI-For-Beginners 12 Weeks, 24 Lessons, AI for All! |
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| Stars | 4,850 | 70,721 |
| Net stars, last 30 days | +46 | +1,056 |
| Largest star day | +9 on Jun 29, 2026 | +2,305 on Aug 1, 2026 |
| Milestone reached in the record | None | 50,000 on Jul 1, 2026 |
| Forks | 834 | 13,786 |
| Language | Jupyter Notebook | Jupyter Notebook |
| License | Other license | MIT |
| Created | Apr 30, 2018 | Mar 3, 2021 |
| Last push | Nov 9, 2026 | Nov 4, 2026 |
| Archived | No | No |
| Health facts: Maintenance | 2 of 4 checks (2 without data) | 4 of 4 checks |
| Health facts: Releases | 2 of 3 checks (1 without data) | 0 of 3 checks (1 without data) |
| Health facts: Security practice | 0 of 1 check (1 without data) | 1 of 1 check |
| Health facts: Community files | 1 of 3 checks (2 without data) | 3 of 3 checks |
| Commits, last 13 weeks | No data | 95 |
| Weeks with commits, last 52 | No data | 40 of 52 |
| In the Repository Index since | Nov 10, 2026 | Oct 22, 2026 |
Topics that all of them have on the Repository Host: machine-learning. The facts come from the Repository Host and from the Star History that AwesomeRepos records. A shared topic does not mean that one repository can replace another. Each Health Facts row is one dimension alone. AwesomeRepos does not add them into one score. How each check is defined