ML Models

An ML Model represents a machine learning model registered within an ML Model Service. It captures metadata such as algorithm, features, hyperparameters, and lineage.

Entity schema follows the OpenMetadata Standard.

Entity Hierarchy

ML Models belong to an ML Model Service:

MlModelService
└── MlModel (this page)

Fully Qualified Name

The FQN format for an ML model is:

service.modelName

For example: mlflow_svc.customer_segmentation

API Endpoints

Method	Endpoint	Description
`PUT`	`/v1/mlmodels`	Create or update an ML model
`POST`	`/v1/mlmodels`	Create an ML model (POST variant)
`GET`	`/v1/mlmodels`	List ML models
`GET`	`/v1/mlmodels/{id}`	Get by ID
`GET`	`/v1/mlmodels/name/{fqn}`	Get by FQN
`PATCH`	`/v1/mlmodels/{id}`	Update by ID
`PATCH`	`/v1/mlmodels/name/{fqn}`	Update by name
`DELETE`	`/v1/mlmodels/{id}`	Delete by ID
`DELETE`	`/v1/mlmodels/name/{fqn}`	Delete by name
`PUT`	`/v1/mlmodels/restore`	Restore soft-deleted ML model
`GET`	`/v1/mlmodels/{id}/versions`	List versions
`GET`	`/v1/mlmodels/{id}/versions/{version}`	Get specific version
`PUT`	`/v1/mlmodels/{id}/followers`	Add follower
`DELETE`	`/v1/mlmodels/{id}/followers/{userId}`	Remove follower
`PUT`	`/v1/mlmodels/{id}/vote`	Add/update vote

ML Model Service Versions

Create an ML Model

​ML Models

​Entity Hierarchy

​Fully Qualified Name

​API Endpoints

ML Models

Entity Hierarchy

Fully Qualified Name

API Endpoints