MLOps-Model-Monitoring rilufiyy · PARTIAL
This project implements an end-to-end MLOps pipeline for house price prediction using MLflow, FastAPI, and Docker. It focuses on modular code design, experiment tracking, model monitoring, structured logging, and production-ready model deployment.
github.com/rilufiyy/MLOps-Model-Monitoring · ★ 0 · Forks 1 · Size 2.3 MB
SUMMARY
Technologies 14
Scored 13
Observed 13
Practices 6
Evidence 15
Skips 1
COVERAGE
Analyzed 113 files · 13 commits · 0 API calls
TECHNOLOGIES & DEPTH
Dockerfile LANGUAGE Depth 70
1 files · PRODUCTION
JSON LANGUAGE Depth 70
1 files · PRODUCTION
Markdown LANGUAGE Depth 70
1 files · PRODUCTION
YAML LANGUAGE Depth 70
12 files · PRODUCTION
Python LANGUAGE Depth 70
14 files · PRODUCTION
pip BUILD_TOOL Depth 80
1 files · CONFIGURATION
FastAPI FRAMEWORK Depth 58
1 files · PRODUCTION
NumPy LIBRARY Depth 70
3 files · PRODUCTION
Pydantic LIBRARY Depth 58
1 files · PRODUCTION
RabbitMQ MESSAGE_BROKER Depth 65
1 files · CONFIGURATION
Requests LIBRARY Depth 62
2 files · PRODUCTION
TypeScript LANGUAGE Depth 58
1 files · PRODUCTION
Uvicorn LIBRARY Depth —
0 files · config only
pandas LIBRARY Depth 78
5 files · PRODUCTION
PRACTICES
documentation · observedautomated_tests · observedcontinuous_integration · absentcontainerization · observedlinting · absentformatting · absent
ACTIVITY & OWNERSHIP
First commit 2026-02-03
Last commit 2026-02-24
Active months 1
Commits 13