Learn the two essential properties you need to define when creating a persistent Azure Machine Learning compute cluster for a training job using the Python SDK v2.
Table of Contents
Question
You manage an Azure Machine Learning workspace.
You must create and configure a compute cluster for a training job by using Python SDK v2.
You need to create a persistent Azure Machine Learning compute resource, specifying the fewest possible properties.
Which two properties should you define? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
A. size
B. win_instances
C. type
D. name
E. max_instances
Answer
C. type
D. name
Explanation
To create a persistent Azure Machine Learning compute cluster for a training job using the Python SDK v2, you need to specify two key properties:
D. name
This property defines the name of the compute cluster. Providing a unique and descriptive name allows you to easily identify and manage the compute resource within your Azure Machine Learning workspace.
C. type
The type property specifies the type of compute resource you want to create. For a compute cluster, you should set the type to “AmlCompute”. This indicates that you are creating an Azure Machine Learning Compute cluster, which is a managed compute infrastructure for training machine learning models.
While properties like size, max_instances, and vm_instances can be used to further configure the compute cluster, they are not strictly required when creating the resource with the minimum necessary properties.
In summary, to create a persistent Azure Machine Learning compute cluster for a training job using Python SDK v2, you must define the name and type properties. These two properties are essential for establishing the identity and nature of the compute resource within your workspace.
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