A versioned model asset in Azure Machine Learning, typed as custom_model, mlflow_model or triton_model, with tags and lineage to the producing job. Registering under the same name again increments the version automatically.
Also called model asset.
Read more: Microsoft Learn
In the Ultra Transcenders books
Each book explains Registered model in context, with comparison tables and the common traps.
Terms in this definition
- Azure Machine Learning
Azure platform where you train, deploy, monitor and retrain models of your own, practising MLOps through tools such as pipelines, online endpoints, model monitoring and prompt flow.
- MLflow model
When a model is stored in MLflow format, with an MLmodel file and conda requirements, you can deploy it to batch or online endpoints with no scoring script or environment of your own.
- Image tagging
An Image Analysis feature producing single-word tags, each with a confidence score, for actions, scenery, objects and living things in an image.
- Job
A sequence of steps executed together on one agent or runner, or on the server for agentless work. While running, each occupies one of your parallel jobs.
Related terms
- CREATE MODEL VERSION
Allows someone to add versions to a registered model in Unity Catalog. Treat it with care: each new version can set off a deployment job under the owner's credentials, giving the holder a route to running any code there.
- EXECUTE
Allows calling a function or loading a registered model in Unity Catalog, and seeing its definition.
USE CATALOGandUSE SCHEMAare needed too. - Model alias
A label such as
@Championthat points to a specific version of a Unity Catalog registered model. Because it can be moved, workloads load the label and avoid hard-coding a number.