deploying-machine-learning-models satya00089 · PARTIAL
Code for the online course "Deployment of Machine Learning Models"
github.com/satya00089/deploying-machine-learning-models · ★ 0 · Forks 0 · Size 5.3 MB
SUMMARY
Technologies 19
Scored 17
Observed 17
Practices 6
Evidence 28
Skips 2
COVERAGE
Analyzed 222 files · 52 commits · 0 API calls
TECHNOLOGIES & DEPTH
Dockerfile LANGUAGE Depth 70
2 files · PRODUCTION
Shell LANGUAGE Depth 70
6 files · PRODUCTION
JSON LANGUAGE Depth 70
1 files · PRODUCTION
TOML LANGUAGE Depth 70
3 files · PRODUCTION
Markdown LANGUAGE Depth 70
2 files · PRODUCTION
YAML LANGUAGE Depth 70
5 files · PRODUCTION
Python LANGUAGE Depth 70
132 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
FastAPI FRAMEWORK Depth 81
12 files · PRODUCTION, TEST
Flask FRAMEWORK Depth 62
2 files · PRODUCTION
NumPy LIBRARY Depth 85
24 files · PRODUCTION, TEST
Pydantic LIBRARY Depth 100
15 files · CONFIGURATION, PRODUCTION
Uvicorn LIBRARY Depth 73
3 files · PRODUCTION
Werkzeug LIBRARY Depth 58
1 files · PRODUCTION
mypy QUALITY Depth —
0 files · config only
pandas LIBRARY Depth 100
31 files · CONFIGURATION, PRODUCTION, TEST
pytest TESTING Depth 85
9 files · PRODUCTION, TEST
PRACTICES
documentation · observedautomated_tests · observedcontinuous_integration · absentcontainerization · observedlinting · observedformatting · absent
ACTIVITY & OWNERSHIP
First commit 2019-01-09
Last commit 2023-04-19
Active months 15
Commits 52