GitHub / kletobias / advanced-mlops-lifecycle-hydra-mlflow-optuna-dvc
End-to-end MLOps pipeline showcasing senior-level best practices with Hydra for configuration, MLflow for experiment tracking, Optuna for hyperparameter tuning, and DVC for data/version control. This repository focuses on reproducibility, modular design, and streamlined collaboration—an ideal demonstration of advanced MLOps capabilities.
JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kletobias%2Fadvanced-mlops-lifecycle-hydra-mlflow-optuna-dvc
PURL: pkg:github/kletobias/advanced-mlops-lifecycle-hydra-mlflow-optuna-dvc
Stars: 2
Forks: 0
Open issues: 0
License: None
Language: Python
Size: 1.18 MB
Dependencies parsed at: Pending
Created at: 4 months ago
Updated at: about 1 month ago
Pushed at: 2 months ago
Last synced at: 4 days ago
Topics: advanced-ml, data-versioning, dry, dvc, end-to-end-ml-workflows, hydra, mlflow, mlops, modular-code, optuna, pipelines, python, reproducibility