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).
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.
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.
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