Complete-ML-Pipeline dhruvXcode247 · COMPLETED
This project covers the end to end understanding for creating an ML pipeline and working around it using DVC for experiment tracking and data versioning using AWS S3
github.com/dhruvXcode247/Complete-ML-Pipeline · ★ 0 · Forks 0 · Size 293 KB
SUMMARY
Technologies 7
Scored 7
Observed 7
Practices 6
Evidence 7
Skips 0
COVERAGE
Analyzed 16 files · 11 commits · 0 API calls
TECHNOLOGIES & DEPTH
Markdown LANGUAGE Depth 70
1 files · PRODUCTION
YAML LANGUAGE Depth 70
2 files · PRODUCTION
Python LANGUAGE Depth 70
5 files · PRODUCTION
NumPy LIBRARY Depth 62
2 files · PRODUCTION
RabbitMQ MESSAGE_BROKER Depth 61
1 files · CONFIGURATION
Redis CACHE Depth 61
1 files · CONFIGURATION
pandas LIBRARY Depth 74
5 files · PRODUCTION
PRACTICES
documentation · observedautomated_tests · absentcontinuous_integration · absentcontainerization · absentlinting · absentformatting · absent
ACTIVITY & OWNERSHIP
First commit 2026-06-15
Last commit 2026-08-10
Active months 2
Commits 11