ML-AI-Algorithms-from-scratch Mattral · PARTIAL
60+ ML/AI/DL/RL/Bayesian algorithms implemented from scratch in NumPy -- plus mlscratch, a pip-installable package (pip install scratchkit) with a consistent, scikit-learn-style API and 1,100+ tests.
github.com/Mattral/ML-AI-Algorithms-from-scratch · ★ 39 · Forks 6 · Size 4.4 MB
SUMMARY
Technologies 14
Scored 11
Observed 11
Practices 6
Evidence 16
Skips 3
COVERAGE
Analyzed 275 files · 138 commits · 0 API calls
TECHNOLOGIES & DEPTH
TOML LANGUAGE Depth 70
1 files · PRODUCTION
Markdown LANGUAGE Depth 70
49 files · PRODUCTION
YAML LANGUAGE Depth 70
2 files · PRODUCTION
Python LANGUAGE Depth 70
195 files · PRODUCTION
pip BUILD_TOOL Depth 80
1 files · CONFIGURATION
Poetry BUILD_TOOL Depth 80
1 files · CONFIGURATION
Black QUALITY Depth —
0 files · config only
NumPy LIBRARY Depth 85
170 files · PRODUCTION, TEST
RabbitMQ MESSAGE_BROKER Depth 73
3 files · CONFIGURATION
Ruff QUALITY Depth —
0 files · config only
TypeScript LANGUAGE Depth 66
3 files · PRODUCTION
mypy QUALITY Depth —
0 files · config only
pandas LIBRARY Depth 85
24 files · PRODUCTION
pytest TESTING Depth 74
51 files · PRODUCTION, TEST
PRACTICES
documentation · observedautomated_tests · observedcontinuous_integration · observedcontainerization · absentlinting · observedformatting · absent
ACTIVITY & OWNERSHIP
First commit 2023-12-08
Last commit 2026-06-22
Active months 6
Commits 138