Question 56
You are performing a classification task in Azure Machine learning Studio.
You must prepare balanced testing and training samples based on a provided data set.
Warning samples based on a provided data set.
You need to split the data with a 0.75:0.25.
Which value should you use for each parameter? To answer, select the appropriate options m the answer area.
NOTE: Each correct selection is worth one point.
You must prepare balanced testing and training samples based on a provided data set.
Warning samples based on a provided data set.
You need to split the data with a 0.75:0.25.
Which value should you use for each parameter? To answer, select the appropriate options m the answer area.
NOTE: Each correct selection is worth one point.
Question 57
You train and register a model in your Azure Machine Learning workspace.
You must publish a pipeline that enables client applications to use the model for batch inferencing. You must use a pipeline with a single ParallelRunStep step that runs a Python inferencing script to get predictions from the input data.
You need to create the inferencing script for the ParallelRunStep pipeline step.
Which two functions should you include? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
You must publish a pipeline that enables client applications to use the model for batch inferencing. You must use a pipeline with a single ParallelRunStep step that runs a Python inferencing script to get predictions from the input data.
You need to create the inferencing script for the ParallelRunStep pipeline step.
Which two functions should you include? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Question 58
Your team is building a data engineering and data science development environment.
The environment must support the following requirements:
support Python and Scala
compose data storage, movement, and processing services into automated data pipelines the same tool should be used for the orchestration of both data engineering and data science support workload isolation and interactive workloads enable scaling across a cluster of machines You need to create the environment.
What should you do?
The environment must support the following requirements:
support Python and Scala
compose data storage, movement, and processing services into automated data pipelines the same tool should be used for the orchestration of both data engineering and data science support workload isolation and interactive workloads enable scaling across a cluster of machines You need to create the environment.
What should you do?
Question 59
You create a machine learning model by using the Azure Machine Learning designer. You publish the model as a real-time service on an Azure Kubernetes Service (AKS) inference compute cluster. You make no change to the deployed endpoint configuration.
You need to provide application developers with the information they need to consume the endpoint.
Which two values should you provide to application developers? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
You need to provide application developers with the information they need to consume the endpoint.
Which two values should you provide to application developers? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Question 60
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?