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.

Register option for a model on the Model tab

  • The Register dialog box appears to confirm the action.

  • Click the Yes option.

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  • A notification message appears to inform the same.

Please Note: The registered 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 performs the same task.​ The Registered Models can be accessed within the DS Lab Model Runner

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

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