B. a compute resource
Explanation:
Before running an Azure Machine Learning designer pipeline, you need a compute resource to execute the pipeline steps. This compute resource provides the necessary processing power for data transformation, training, and inference tasks.
A registered model (Option A) is needed after training a model, but it's not required to run the pipeline initially.
A Jupyter notebook (Option C) is useful for scripting and experimentation but is not required for running a pipeline in Azure ML designer.
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