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NEW QUESTION: 1
会社が新しいネットワークロードバランサー（NLB）（または既存のインターフェイスVPCエンドポイントを作成したい。SysOps管理者は既存のNLBを削除しようとしましたが、「既存のVPCエンドポイント接続と削除できません」というエラーが表示されます。これを解決するソリューションはどれですか。問題？
A. 新しいNLBを作成します。インターフェイスエンドポイントサービスによって使用されているNLBの関連付けを解除します。新しいNLBをインターフェイスエンドポイントサービスに関連付けます。
B. 新しいインターフェースエンドポイントを作成します。既存のNLBを新しいインターフェイスエンドポイントに移動します。古いエンドポイントのNLBを新しいNLBに置き換えます。
C. インターフェースエンドポイント接続を拒否します。 NLBの関連付けを解除します。新しいNLBを作成し、それをインターフェイスエンドポイントに関連付けます。
D. インターフェイスエンドポイントサービスによって使用されているNLBの関連付けを解除します。新しいNLBを作成し、それをインターフェイスエンドポイントに関連付けます。
Answer: C
NEW QUESTION: 2
グローバルサービス担当者がLightningサービスコンソール内から顧客に電話をかけることができるようにコンサルタントが設定する必要がある機能はどれですか。
A. マクロ
B. ローカルプレゼンス
C. ライトニングダイヤラ
D. Open CTI
Answer: C
NEW QUESTION: 3
Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is exactly the same in each question in this series.
Start of repeated scenario
You plan to use Azure platform tools to detect and analyze food items in smart refrigerators. To provide families with an integrated experience for grocery shopping and cooking, the refrigerators will connect to other smart appliances, such as stoves and microwave ovens, on a LAN.
You plan to build an object recognition model by using the Microsoft Cognitive Toolkit. The object recognition model will receive input from the connected devices and send results to applications.
The training data will be derived from more than 10 TB of images. You will convert the raw images to the sparse format.
End of repeated scenario.
You need to preprocess the training data by using a Principal Component Analysis (PCA) algorithm in the least amount of time possible. Which implementation method should you use?
A. Azure Machine Learning Studio and a custom Execute Python Script module
B. Azure Machine Learning Studio with a custom Execute R Script module
C. Azure HDInsight using HiveML
D. Azure HDInsight using Microsoft R Server
Answer: D