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NEW QUESTION: 1
Nancy is the project manager of a project with 78 stakeholders. This is a high-profile project and she needs to express to her project team and to the management the importance of communication in this project. She would like to show the number of stakeholder communication channels in the project. Based on this information how many communication channels exist within this project?
A. 3,003
B. 6,084
C. 0
D. 1
Answer: A
NEW QUESTION: 2
You have an Azure subscription named Subscription1 that has a subscription ID of c276fc76-9cd4-44c9-99a7-4fd71546436e.
You need to create a custom RBAC role named CR1 that meets the following requirements:
Can be assigned only to the resource groups in Subscription1
Prevents the management of the access permissions for the resource groups Allows the viewing, creating, modifying, and deleting of resource within the resource groups What should you specify in the assignable scopes and the permission elements of the definition of CR1? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Box 1: "/subscription/c276fc76-9cd4-44c9-99a7-4fd71546436e"
In the assignableScopes you need to mention the subscription ID where you want to implement the RBAC Box 2: "Microsoft.Authorization/*" Microsoft.Authorization/* is used to Manage authorization References:
https://docs.microsoft.com/en-us/azure/role-based-access-control/resource-provider-operations#microsoftauthorization
https://docs.microsoft.com/en-us/azure/role-based-access-control/built-in-roles
References:
https://docs.microsoft.com/en-us/azure/role-based-access-control/custom-roles
https://docs.microsoft.com/en-us/azure/role-based-access-control/resource-provider-operations#microsoftresources
NEW QUESTION: 3
あなたの会社の事業主はあなたに銀行取引のデータベースを与えました。各行には、ユーザーID、トランザクションタイプ、トランザクションの場所、およびトランザクションの金額が含まれています。データに適用できる機械学習の種類を調査するように求められます。どの3つの機械学習アプリケーションを使用できますか？ （3つ選択してください。）
A. どのトランザクションが不正である可能性が最も高いかを判断するための教師なし学習。
B. トランザクションの場所を予測するための教師なし学習。
C. トランザクションの場所を予測するための強化学習。
D. どのトランザクションが不正である可能性が最も高いかを判断するための教師あり学習。
E. トランザクションの場所を予測するための教師あり学習。
F. 機能の類似性に基づいてトランザクションをN個のカテゴリに分割するクラスタリング。
Answer: A,C,F