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NEW QUESTION: 1
Your customer wants to change the label 'employee' to associate throughout the SuccessFactors Learning system.
Where do you perform the first step to change this label?
Please choose the correct answer.
Response:
A. References -> Geography -> Labels -> Search and edit
B. System Admin -> Tools -> Label import/export -> Export
C. References -> Geography -> Labels -> Add New
D. System Admin -> Tools -> Label import/export -> Import
Answer: D

NEW QUESTION: 2
Which two Amazon services can be used for storage? (Choose two.)
A. Amazon RedShift
B. Amazon Glacier
C. Amazon Simple Storage Service (S3)
D. Amazon CloudWatch
E. Amazon Virtual Private Cloud (VPC)
Answer: B,C

NEW QUESTION: 3
STOPPED状態でインスタンスの課金が発生しないOracle Cloud Infrastructureのコンピューティング形状はどれですか？
A. HPC
B. 高密度I / O
C. GPU
D. 標準
Answer: D
Explanation:
ExplanationA shape is a template that determines the number of CPUs, amount of memory, and other resources that are allocated to an instance.
Standard shapes don't incur costs in a STOPPED state.

NEW QUESTION: 4
You deploy a model in Azure Container Instance.
You must use the Azure Machine Learning SDK to call the model API.
You need to invoke the deployed model using native SDK classes and methods.
How should you complete the command? To answer, select the appropriate options in the answer areas.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation:
Box 1: from azureml.core.webservice import Webservice
The following code shows how to use the SDK to update the model, environment, and entry script for a web service to Azure Container Instances:
from azureml.core import Environment
from azureml.core.webservice import Webservice
from azureml.core.model import Model, InferenceConfig
Box 2: predictions = service.run(input_json)
Example: The following code demonstrates sending data to the service:
import json
test_sample = json.dumps({'data': [
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
[10, 9, 8, 7, 6, 5, 4, 3, 2, 1]
]})
test_sample = bytes(test_sample, encoding='utf8')
prediction = service.run(input_data=test_sample)
print(prediction)
Reference:
https://docs.microsoft.com/bs-latn-ba/azure/machine-learning/how-to-deploy-azure-container-instance
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-deployment