Register a Model

To register a model implies pushing the model into the Pipeline environment where it can be used for inferencing when Production data is read.

Please Note: The currently supported model types are: Sklearn (ML & CV), Keras (ML & CV), and PyTorch (ML).

Check out the walk-through to Register a Data Science model to the Data Pipeline (from the Model tab).

Registering a Model

The user can export a saved DSL model to the Data Pipeline module from the Models tab.

• Navigate to the Models tab.

• Select a model (unregistered model) from the list.

• Click the Register icon for the model.

Register option for a model on the Model tab

• The Register dialog box appears to confirm the action.

• Click the Yes option.

​

• A notification message appears to inform the same.

Please Note: The registered model gets published to the Data Pipeline (it is moved to the Registered list of the models).

• The model gets listed under the Registered model list.

Please Note:

• The Register option is also available under the Models section inside a Data Science Notebook.​

• The Registered Models can be accessed within the DS Lab Model Runner component of the Data Pipeline module.