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Stars gained: From Apr 26, 2026 to Nov 4, 2026, each from zeroStars gainedFrom Apr 26, 2026 to Nov 4, 2026, each from zero01K2KApr 26Nov 4, 2026hachmannlab/chemmleriklindernoren/ML-From-Scratch
Stars: The star count at the end of each dayStarsThe star count at the end of each day020KApr 25Nov 4, 2026hachmannlab/chemmleriklindernoren/ML-From-Scratch

Facts

Facthachmannlab/chemml

ChemML is a machine learning and informatics program suite for the chemical and materials sciences.

eriklindernoren/ML-From-Scratch

Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.

Stars18033,269
Net stars, last 30 days+1+349
Largest star day+1 on May 17, 2026+172 on May 31, 2026
Milestone reached in the recordNoneNone
Forks335,539
LanguagePythonPython
LicenseBSD-3-CLAUSEMIT
CreatedDec 7, 2017Feb 5, 2017
Last pushNov 4, 2026Oct 15, 2023
ArchivedNoNo
Health facts: Maintenance2 of 4 checks (2 without data)1 of 4 checks
Health facts: Releases2 of 3 checks (1 without data)0 of 3 checks (1 without data)
Health facts: Security practice0 of 1 check (1 without data)0 of 1 check
Health facts: Community files1 of 3 checks (2 without data)1 of 3 checks
Commits, last 13 weeksNo data0
Weeks with commits, last 52No data0 of 52
In the Repository Index sinceOct 22, 2026Oct 22, 2026

Topics that all of them have on the Repository Host: data-science, machine-learning, deep-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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