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).
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.
The Deploy to Pipeline dialog box appears to confirm the action.
Click the Yes option.
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.
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