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NEW QUESTION: 1
新しいAzureサブスクリプションを作成します。サブスクリプションでリソースはプロビジョニングされません。
Azure Machine Learningワークスペースを作成する必要があります。
この目標を達成するための3つの可能な方法は何ですか？それぞれの正解は完全なソリューションを示します。
注：それぞれの正しい選択は1ポイントの価値があります。
A. Azure ML SDKライブラリを使用するPythonコードを実行し、names、subscriptionjd、resource_group、およびlocationパラメーターを指定してWorkspacesreateメソッドを呼び出します。
B. Azure Machine Learning拡張機能でAzureコマンドラインインターフェイス（CLI）を使用して、-nameおよび-locationパラメーターを指定してaz group create関数を呼び出し、次に-wおよび-gパラメーターを指定してaz ml workspace create関数を呼び出します。ワークスペース名とリソースグループ。
C. Azure Machine Learning Studioに移動し、ワークスペースを作成します。
D. Azure ML SDKライブラリを使用して、name、subscriptionjd、およびresource.groupパラメーターを指定してWorkspace.getメソッドを呼び出すPythonコードを実行します。
E. 次を含むAzureリソース管理テンプレートを使用します
Microsoft.MachineLearningServices / workspacesリソースとその依存関係。
Answer: A,C,D
NEW QUESTION: 2
A. Option D
B. Option B
C. Option E
D. Option A
E. Option C
Answer: B,E
NEW QUESTION: 3
동료가 AWS에서 3 계층 LAMP (Linux, Apache, MySQL, PHP) 애플리케이션을 쉽게 배포, 모니터링 및 확장하는 방법에 대한 조언을 요청했습니다. 동료는 시간과 인력 제한이 있으며 최소한의 노력으로 응용 프로그램을 배포하고 관리하려고 합니다.
어떤 AWS 서비스를 제안 하시겠습니까?
A. CloudFormation
B. CodeDeploy
C. Elastic Beanstalk
D. Data Pipeline
Answer: B
Explanation:
Explanation
AWS CodeDeploy automates code deployments to any instance, including Amazon EC2 instances and on-premises servers. AWS CodeDeploy makes it easier for you to rapidly release new features, helps you avoid downtime during application deployment, and handles the complexity of updating your applications.