You plan to implement an Azure Machine Learning solution. You have the following requirements:
• Run a Jupyter notebook to interactively tram a machine learning model.
• Deploy assets and workflows for machine learning proof of concept by using scripting rather than custom programming.
You need to select a development technique for each requirement
Which development technique should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
You need to record the row count as a metric named row_count that can be returned using the get_metrics method of the Run object after the experiment run completes. Which code should you use?
You have an Azure Machine Learning workspace. You build a deep learning model.
You need to publish a GPU-enabled model as a web service.
Which two compute targets can you use? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
You are using Azure Machine Learning to train machine learning models. You need a compute target on which to remotely run the training script. You run the following Python code: