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NEW QUESTION: 1
What can a customer do with a Group entity in the SuccessFactorss Learning systems? Note: There are 3 correct answers to this question.
A. Reserve slots in a scheduled offering for the Group
B. Associate a Questionnaire Survey to the Group
C. Manually add users to the Group
D. Use an assignment profile to identity the users that belong to the Group
E. Create a custom tile that displays only to the Group
Answer: A,D,E

NEW QUESTION: 2
Refer to the exhibit.

Which route type does the routing protocol Code D represent in the output?
A. route learned through EIGRP
B. statically assigned route
C. /24 route of a locally configured IP
D. internal BGP route
Answer: A

NEW QUESTION: 3
You use Azure Machine Learning to train and register a model.
You must deploy the model into production as a real-time web service to an inference cluster named service-compute that the IT department has created in the Azure Machine Learning workspace.
Client applications consuming the deployed web service must be authenticated based on their Azure Active Directory service principal.
You need to write a script that uses the Azure Machine Learning SDK to deploy the model. The necessary modules have been imported.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation

Box 1: AksCompute
Example:
aks_target = AksCompute(ws,"myaks")
# If deploying to a cluster configured for dev/test, ensure that it was created with enough
# cores and memory to handle this deployment configuration. Note that memory is also used by
# things such as dependencies and AML components.
deployment_config = AksWebservice.deploy_configuration(cpu_cores = 1, memory_gb = 1) service = Model.deploy(ws, "myservice", [model], inference_config, deployment_config, aks_target) Box 2: AksWebservice Box 3: token_auth_enabled=Yes Whether or not token auth is enabled for the Webservice.
Note: A Service principal defined in Azure Active Directory (Azure AD) can act as a principal on which authentication and authorization policies can be enforced in Azure Databricks.
The Azure Active Directory Authentication Library (ADAL) can be used to programmatically get an Azure AD access token for a user.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-deploy-azure-kubernetes-service
https://docs.microsoft.com/en-us/azure/databricks/dev-tools/api/latest/aad/service-prin-aad-token

NEW QUESTION: 4
DRAG DROP


Answer:
Explanation: