Compare repositories
This page shows the Star History and the facts of 2 to 5 repositories in the Repository Index, side by side. You choose the repositories. The page does not rank them.
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. | unslothai/hyperlearn 2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old. |
|---|---|---|
| Stars | 4,850 | 2,531 |
| Net stars, last 30 days | +46 | +7 |
| Largest star day | +9 on Jun 29, 2026 | +3 on May 16, 2026 |
| Milestone reached in the record | None | None |
| Forks | 834 | 169 |
| Language | Jupyter Notebook | Jupyter Notebook |
| License | Other license | APACHE-2.0 |
| Created | Apr 30, 2018 | Aug 27, 2018 |
| Last push | Nov 9, 2026 | Nov 19, 2024 |
| Archived | No | No |
| Health facts: Maintenance | 2 of 4 checks (2 without data) | 1 of 4 checks (2 without data) |
| Health facts: Releases | 2 of 3 checks (1 without data) | 0 of 3 checks (2 without data) |
| Health facts: Security practice | 0 of 1 check (1 without data) | 0 of 1 check (1 without data) |
| Health facts: Community files | 1 of 3 checks (2 without data) | 1 of 3 checks (2 without data) |
| Commits, last 13 weeks | No data | No data |
| Weeks with commits, last 52 | No data | No data |
| In the Repository Index since | Nov 10, 2026 | Oct 22, 2026 |
Topics that all of them have on the Repository Host: machine-learning, econometrics. 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