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NEW QUESTION: 1
Amazon Elastic File System (EFS) provides information about the space used for an object by using the space _ used attribute of the Network File System Version 4.1 (NFSv4.1). The attribute includes the object's current metered data size and not the metadata size. Which of the following utilities will you use to measure the amount of disk that is used of a file?
A. du utility
B. sfdisk utility
C. pydf utility
D. blkid utility
Answer: A
Explanation:
Explanation/Reference:
Explanation:
Amazon EFS reports file system sizes and sizes of objects within a file system. Using the NFSv4.1 space
_ used attribute for measuring the space used for an object, it reports only the object's current metered data size and not the metadata size. There are two utilities available for measuring disk usage of a file, the du and stat utilities.
https://docs.aws.amazon.com/efs/latest/ug/metered-sizes.html

NEW QUESTION: 2
Drag the recommendations on the left to the Cryptographic Algorithms on the right. Options will be used more than once.

Answer:
Explanation:

Explanation
DES = Avoid
3DES = Legacy
MD5 = Avoid
SHA-1 = Legacy
HMAC-MD5 = Legacy
https://www.cisco.com/c/en/us/about/security-center/next-generation-cryptography.html

NEW QUESTION: 3
注:この質問は、同じシナリオを提示する一連の質問の一部です。シリーズの各質問には、述べられた目標を達成する可能性のある独自の解決策が含まれています。一部の質問セットには複数の正しい解決策がある場合がありますが、他の質問セットには正しい解決策がない場合があります。
このセクションの質問に回答した後は、その質問に戻ることはできません。その結果、これらの質問はレビュー画面に表示されません。
Pythonスクリプトを使用して、Azure MachineLearningの実験を実行することを計画しています。スクリプトは、実験実行コンテキストへの参照を作成し、ファイルからデータをロードし、ラベル列の一意の値のセットを識別して、実験実行を完了します。
azureml.coreからインポート実行
パンダをpdとしてインポートする
run = Run.get_context()
データ= pd.read_csv( 'data.csv')
label_vals = data ['label']。unique()
#ここに指標を記録するコードを追加
run.complete()
実験では、後で確認できる実行のメトリックとして、データ内の一意のラベルを記録する必要があります。
コメントで示されたポイントで実行メトリックとして一意のラベル値を記録するには、スクリプトにコードを追加する必要があります。
解決策:コメントを次のコードに置き換えます。
label_valsのlabel_valの場合:
run.log( 'ラベル値'、label_val)
ソリューションは目標を達成していますか?
A. いいえ
B. はい
Answer: B
Explanation:
The run_log function is used to log the contents in label_vals:
for label_val in label_vals:
run.log('Label Values', label_val)
Reference:
https://www.element61.be/en/resource/azure-machine-learning-services-complete-toolbox-ai