How to Version ML Datasets and Experiments With DVC and MLflow: A DevOps Engineer’s Guide
By KP | TZoneLabs | DevOps & Cloud Engineering Put the dataset under DVC, point it at an S3 bucket with versioning turned on, and log every training run to MLflow with the data version attached as a tag. That gives a model the same traceability Git gives code: for any model in production, we … Read more