HOTSPOT – 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…

QuestionsCategory: DP-100HOTSPOT – 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…
Admin Staff asked 4 months ago
HOTSPOT -
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.
Hot Area:
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Suggested Answer: 
    Correct Answer Image

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

This question is in DP-100 Exam
For getting Microsoft Azure Data Scientist Associate Certificate


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