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NEW QUESTION: 1
開発チームは、新しいアプリケーションにAWSCodePipehneとAWSCodeCommitを使用して、継続的インテグレーション/継続的デリバリー（CI / CD）プロセスを採用することを決定しました。ただし、管理者は、コードを本番環境に展開する前に、コードを確認して承認することを求めています。開発チームは、CI / CDパイプラインに手動の承認者を追加するにはどうすればよいですか。
A. パイプラインに承認アクションを追加します。承認が必要なときにAmazonSNSトピックに公開するように承認アクションを設定します。パイプラインの実行は停止し、承認を待ちます
B. CodeCommitに承認ステップを追加します。コミットは承認されるまで保存されません。
C. 承認された場合、CodeCommitリポジトリに変更をプッシュするときに承認されたタグを追加します。 CodePipeiineは、承認されたコミットの構築と展開を中断することなく続行します
D. AWS SESを使用して、アクションが必要なときに承認者にメールを送信します承認者がビルドを承認または拒否できるようにするシンプルなアプリケーションを開発しますビルドが承認されたときにパイプラインを進めるためにAWSLambda関数を呼び出します
Answer: A

NEW QUESTION: 2
You have a print server that runs Windows Server 2003 Service Pack 2 (SP2).
You need to receive a notification each time a document fails to print.
What should you do?
A. From the Services console, enable and configure the Messenger service.
B. From the Performance console, create an alert.
C. From the Event Viewer console, create a new filter.
D. From the Printer Server properties, modify the Advanced settings.
Answer: B

NEW QUESTION: 3
You are solving a classification task.
You must evaluate your model on a limited data sample by using k-fold cross validation. You start by configuring a k parameter as the number of splits.
You need to configure the k parameter for the cross-validation.
Which value should you use?
A. k=5
B. k=1
C. k=0.5
D. k=0
Answer: A
Explanation:
Explanation/Reference:
Explanation:
Leave One Out (LOO) cross-validation
Setting K = n (the number of observations) yields n-fold and is called leave-one out cross-validation (LOO), a special case of the K-fold approach.
LOO CV is sometimes useful but typically doesn't shake up the data enough. The estimates from each fold are highly correlated and hence their average can have high variance.
This is why the usual choice is K=5 or 10. It provides a good compromise for the bias-variance tradeoff.