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NEW QUESTION: 1
ユニバーサルコンテナーは、レガシーシステムからサービスクラウドに移行しています。同社は現在、レガシーシステムでの契約として資格を追跡しています。レガシーシステムはアーカイブされ、稼働後は使用できなくなります。エージェントは、過去1年間のケース情報に簡単にアクセスできる必要があります。
A. クローズされたケースをカスタムの読み取り専用オブジェクトに移行します
B. オープンケースとクローズケースをマイルストーンとエンタイトルメントで移行します
C. マイルストーンとエンタイトルメントを使用して、クローズされたケースを移行します
D. マイルストーンとエンタイトルメントなしでオープンケースとクローズケースを移行します
Answer: C
NEW QUESTION: 2
A restore of the QMGR needs to be completed,as an upgrade was not successful. What step need to be completed as part of the restore?
A. Restartthe QMGR
B. Backup the QMGR data
C. Uninstall. the QMGR
D. Recreate the Channels
Answer: A
NEW QUESTION: 3
The internal audit staff lacks the expertise to perform a specific activity when auditing an organization. Which of the following individuals is not an appropriate choice to perform this task?
A. A researcher affiliated with a college or university.
B. A specialist from the staff of a government agency.
C. A consultant from an outside firm.
D. An expert within the department being audited.
Answer: D
NEW QUESTION: 4
あなたはホテル予約のウェブサイト会社で働いているデータサイエンティストです。 Azure Machine Learningサービスを使用して、不正なトランザクションを識別するモデルをトレーニングします。
Azure Machine Learning SDKのModel.deployメソッドを使用して、モデルをAzure Machine LearningリアルタイムWebサービスとしてデプロイする必要があります。デプロイされたWebサービスは、トランザクションデータ入力に基づいて不正のリアルタイム予測を返す必要があります。
モデルのデプロイに使用されるInferenceConfigクラスのentry_scriptパラメーターとして指定されるスクリプトを作成する必要があります。
入力スクリプトは何をすべきですか？
A. Webサービスコンピューティング用のConda環境を作成し、必要なPythonパッケージをインストールします。
B. モデルを読み込み、それを使用して入力データからラベルを予測します。
C. Webサービスがデプロイされている推論クラスターでノードを起動します。
D. 適切なタグとプロパティを使用してモデルを登録します。
E. 推論の計算に必要なコアの数とメモリの量を指定します。
Answer: B
Explanation:
Explanation
The entry script receives data submitted to a deployed web service and passes it to the model. It then takes the response returned by the model and returns that to the client. The script is specific to your model. It must understand the data that the model expects and returns.
The two things you need to accomplish in your entry script are:
Loading your model (using a function called init())
Running your model on input data (using a function called run())
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-deploy-and-where