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NEW QUESTION: 1
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.
Incorrect Answers:
auth_enabled (bool): Whether or not to enable key auth for this Webservice. Defaults to True.
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: 2
During a routine audit of a customer service hotline, an internal auditor noticed that an unusually high number of customer complaints pertained to payments not being applied to the customers' accounts.
Which of the following would most likely be the reason for the high volume of complaints?
A. Submission of fraudulent expense reports.
B. Poor controls in the invoice approval processes.
C. An ineffective customer service department.
D. Check tampering by an employee.
Answer: D

NEW QUESTION: 3
Refer to the exhibit:

An engineer is preparing to implement data plane security configuration.
Which statement about this configuration is true?
A. Router 2 is the router receiving the DDoS attack
B. Router 1 must be configured with uRPF for the RTBH implementation to be effective.
C. Router 2 must configure a route to null 0 for network 192 168.1 0/24 for the RTBH implementation to be complete.
D. Router 1 is the trigger router in a RTBH implementation.
Answer: C

NEW QUESTION: 4
どのベースラインがパフォーマンス測定ベースラインを構成していますか？
A. コストベースライン、スケジュールベースライン、およびリスクベースライン
B. スコープベースライン、コストベースライン、およびスケジュールベースライン
C. スコープベースライン、プロジェクト管理ベースライン、および品質ベースライン
D. コストベースライン、プロジェクト管理ベースライン、およびスケジュールベースライン
Answer: B