Before running a pipeline in Azure Machine Learning Designer, you must have an available compute resource (such as a compute instance or compute cluster). Compute provides the processing power required to train, evaluate, and execute the pipeline’s modules.
Other options:
A. Jupyter notebook – Used for code-first development, not required for Designer pipelines.
B. Registered model – Created after running a pipeline, not before.
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