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NEW QUESTION # 157
You use the Azure Machine Learning SDK in a notebook to run an experiment using a script file in an experiment folder.
The experiment fails.
You need to troubleshoot the failed experiment.
What are two possible ways to achieve this goal? Each correct answer presents a complete solution.
Answer: A,D
Explanation:
Explanation
Use get_details_with_logs() to fetch the run details and logs created by the run.
You can monitor Azure Machine Learning runs and view their logs with the Azure Machine Learning studio.
Reference:
https://docs.microsoft.com/en-us/python/api/azureml-pipeline-core/azureml.pipeline.core.steprun
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-monitor-view-training-logs
NEW QUESTION # 158
A company manufactures automobile parts. The company installs IoT sensors on manufacturing machinery.
You must design a solution that analyzes data from the sensors.
You need to recommend a solution that meets the following requirements:
- Data must be analyzed in real-time.
- Data queries must be deployed using continuous integration.
- Data must be visualized by using charts and graphs.
- Data must be available for ETL operations in the future.
- The solution must support high-volume data ingestion.
Which three actions should you recommend? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Answer: A,C,D
NEW QUESTION # 159
You publish a batch inferencing pipeline that will be used by a business application.
The application developers need to know which information should be submitted to and returned by the REST interface for the published pipeline.
You need to identify the information required in the REST request and returned as a response from the published pipeline.
Which values should you use in the REST request and to expect in the response? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: JSON containing an OAuth bearer token
Specify your authentication header in the request.
To run the pipeline from the REST endpoint, you need an OAuth2 Bearer-type authentication header.
Box 2: JSON containing the experiment name
Add a JSON payload object that has the experiment name.
Example:
rest_endpoint = published_pipeline.endpoint
response = requests.post(rest_endpoint,
headers=auth_header,
json={"ExperimentName": "batch_scoring",
"ParameterAssignments": {"process_count_per_node": 6}})
run_id = response.json()["Id"]
Box 3: JSON containing the run ID
Make the request to trigger the run. Include code to access the Id key from the response dictionary to get the value of the run ID.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/tutorial-pipeline-batch-scoring-classification
NEW QUESTION # 160
You manage an Azure Machine Learning workspace.
You build an image recognition training pipeline, which includes hyperparameter tuning. For each epoch run, you plan to log the following metrics:
* the transformed images used for training in an existing folder
* a description to explain the hyperparameter changes
You need to configure logging for the experiment.
Which two functions should you use? Each correct answer presents part of the solution. Choose two. NOTE: Each correct selection is worth one point.
Answer: C,D
NEW QUESTION # 161
You create an Azure Machine Learning managed compute resource. The compute resource is configured as follows:
- Minimum nodes: 2
- Maximum nodes: 4
You must decrease the minimum number of nodes and increase the maximum number of nodes to the following values:
- Minimum nodes: 0
- Maximum nodes: 8
You need to reconfigure the compute resource.
Which three methods can you use? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
Answer: A,D,E
Explanation:
The compute autoscales down to zero nodes when it isn't used. Dedicated VMs are created to run your jobs as needed. Use the following examples to create a compute cluster:
- Python SDK
- Azure CLI
- Studio
https://learn.microsoft.com/en-us/azure/machine-learning/how-to-create-attach-compute- cluster?view=azureml-api-2&tabs=python#create
NEW QUESTION # 162
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