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NEW QUESTION: 1
外部のプロジェクトリソースは、契約がまもなく期限切れになることをプロジェクトマネージャーに通知します。この情報を確認して問題を解決するために、プロジェクトマネージャーはどのドキュメントを確認する必要がありますか?
A. 組織プロセス資産
B. リソース管理計画
C. プロジェクト契約
D. 組織図
Answer: C
NEW QUESTION: 2
ユーザーがWindowsベースのEC2インスタンスを起動しました。
ただし、インスタンスにはいくつかの問題があり、ユーザーはログを確認したいと考えています。
ユーザーがAWSコンソールからインスタンスコンソールの出力を確認すると、何が表示されますか?
A. Windowsインスタンスはコンソール出力をサポートしません
B. 最新の10件のシステムイベントログエラー
C. インスタンス起動以降のすべてのイベントログ
D. 最後の3つのシステムイベントのログエラー
Answer: D
Explanation:
The AWS EC2 console provides a useful tool called Console output for problem diagnosis. It is useful to find out any kernel issues, termination reasons or service configuration issues. For a Windows instance it lists the last three system event log errors. For Linux it displays the exact console output.
NEW QUESTION: 3
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have a Python script named train.py in a local folder named scripts. The script trains a regression model by using scikit-learn. The script includes code to load a training data file which is also located in the scripts folder.
You must run the script as an Azure ML experiment on a compute cluster named aml-compute.
You need to configure the run to ensure that the environment includes the required packages for model training. You have instantiated a variable named aml-compute that references the target compute cluster.
Solution: Run the following code:
Does the solution meet the goal?
A. No
B. Yes
Answer: A
Explanation:
Explanation
The scikit-learn estimator provides a simple way of launching a scikit-learn training job on a compute target. It is implemented through the SKLearn class, which can be used to support single-node CPU training.
Example:
from azureml.train.sklearn import SKLearn
}
estimator = SKLearn(source_directory=project_folder,
compute_target=compute_target,
entry_script='train_iris.py'
)
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-train-scikit-learn
NEW QUESTION: 4
Given:
What is the result?
A. Compilation fails at line n1 and line n2.
B. Welcome Visit Count:1Welcome Visit Count: 2
C. Welcome Visit Count:1Welcome Visit Count: 2
D. Compilation fails at line n3 and line n4.
Answer: A