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Stars gained: From May 8, 2026 to Nov 11, 2026, each from zeroStars gainedFrom May 8, 2026 to Nov 11, 2026, each from zero010KMay 8Nov 11, 2026py-why/EconMLrasbt/LLMs-from-scratch
Stars: The star count at the end of each dayStarsThe star count at the end of each day050K100KApr 26Nov 11, 2026py-why/EconMLrasbt/LLMs-from-scratch

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.

rasbt/LLMs-from-scratch

Implement a ChatGPT-like LLM in PyTorch from scratch, step by step

Stars 4,850108,254
Net stars, last 30 days +46+1,880
Largest star day +9 on Jun 29, 2026+787 on May 12, 2026
Milestone reached in the record None100,000 on Aug 4, 2026
Forks 83416,734
Language Jupyter NotebookJupyter Notebook
License Other licenseOther license
Created Apr 30, 2018Jul 23, 2023
Last push Nov 9, 2026Nov 9, 2026
Archived NoNo
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)0 of 1 check
Health facts: Community files 1 of 3 checks (2 without data)1 of 3 checks
Commits, last 13 weeks No data29
Weeks with commits, last 52 No data35 of 52
In the Repository Index since Nov 10, 2026Oct 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

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