You have an Azure Machine Learning (ML) model deployed to an online endpoint.
You need to review container logs from the endpoint by using Azure Ml Python SDK v2. The logs must include the console log from the inference server with print/log statements from the models scoring script.
What should you do first?

You manage an Azure Machine Learning workspace named workspaces
You must develop Python SDK v2 code to attach an Azure Synapse Spark pool as a compute target in workspaces The code must invoke the constructor of the SynapseSparkCompute class.
You need to invoke the constructor.
What should you use?

You are preparing to use the Azure ML SDK to run an experiment and need to create compute. You run the following code:

For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

You are designing an Azure Machine Leaning solution by using the Python SDK v2.
You must train and deploy the solution by using a compute target. The compute target must meet the following requirements:
* Enable the use of on-premises compute resources.
* Support autoscalling.
You need to configure a compute target for training and inference.
Which compute target t should you configure?
To answer select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

You are solving a classification task.
You must evaluate your model on a limited data sample by using k-fold cross-validation. You start by configuring a k parameter as the number of splits.
You need to configure the k parameter for the cross-validation.
Which value should you use?