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 DSL model to the Data Pipeline (from the Model tab).

Registering a Model from the Model tab

The user can deploy a saved DSL model to the Data Pipeline plugin by using the Model tab.

• Navigate to the Model tab.

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

• Click the Register icon for the model.

Registering a model from the Model tab

• The Deploy to Pipeline dialog box appears to confirm the action.

• Click the Yes option.

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• A notification message appears to inform the same.

• The selected model gets published to the Data Pipeline (It disappears from the Unregistered model list).

• The model gets listed under the Registered model list.

Please Note:

• The Register option provided under the Notebook tab and Model tab perform the same task.​ The Registered Models can be accessed within the DS Lab Model Runner

• Refer the Data Science Lab Quick Start Flow page to get an overview of the Data Science Lab module in nutshell.