EC

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.

4.6k 802 +3/wk
GitHub
causal-inference causality econometrics economics machine-learning treatment-effects
Trend 3

Star & Fork Trend (19 data points)

Stars
Forks

Multi-Source Signals

Growth Velocity

py-why/EconML has +3 stars this period . 7-day velocity: 0.1%.

Deep analysis is being generated for this repository.

Signal-backed technical analysis will be available soon.

Metric EconML Promptify serenata-de-amor cracking-the-data-science-interview
Stars 4.6k 4.6k4.6k4.6k
Forks 802 3626581.2k
Weekly Growth +3 -2+1+0
Language Jupyter Notebook PythonPythonJupyter Notebook
Sources 1 111
License NOASSERTION Apache-2.0MITN/A

Capability Radar vs Promptify

EconML
Promptify
Maintenance Activity 100

Last code push 2 days ago.

Community Engagement 87

Fork-to-star ratio: 17.5%. Active community forking and contributing.

Issue Burden 70

Issue data not yet available.

Growth Momentum 44

+3 stars this period — 0.07% growth rate.

License Clarity 30

No clear license detected — proceed with caution.

Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.