End-to-end colorectal cancer prediction system using MLflow experiment tracking, DagsHub collaboration, Kubeflow pipelines, Docker, and Kubernetes deployment.
docker kubernetes flask data-science machine-learning data-preprocessing model-evaluation data-ingestion model-training kubeflow mlops mlflow cancer-prediction ml-pipeline healthcare-ai dagshub docker-containerization model-artifact-generation deployment-preparation
-
Updated
Mar 6, 2026 - Jupyter Notebook