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NEW QUESTION: 1
テナントのすべてのユーザーがMicrosoft 365の更新の最も早いリリースにアクセスできることを確認する必要があります。組織のリリース設定を標準リリースに設定します。
下線が引かれたテキストではステートメントが正しくない場合は、正しい答えを選択してください。下線が引かれたテキストでステートメントが正しい場合は、「変更は必要ありません」を選択します。
A. 最初のリリース
B. 一部のユーザーを対象としたリリース
C. 変更は必要ありません
D. 組織全体を対象としたリリース
Answer: D
Explanation:
Standard release is the default setting. It implements updates on final release rather than early release.
First release is now called Targeted release. Targeted release is the early release of updates for early feedback. You can choose to have individuals or the entire organization receive updates early.
https://docs.microsoft.com/en-us/office365/admin/manage/release-options-in-office-365?view=o365-worldwide
NEW QUESTION: 2
個人所有デバイスの持ち込み（BYOD）プログラムを作成する場合、次のことが最も重要です。
A. 組織のデータの所有権とデバイスの管理を確認します。
B. プライベートとビジネスの使用量のコストのバランスを取り、使用量を追跡する方法を定義します。
C. リモートワイプ機能と手順を開発します。
D. プログラムの有効性を評価するための指標を確立します。
Answer: A
NEW QUESTION: 3
You need to use the Python language to build a sampling strategy for the global penalty detection models.
How should you complete the code segment? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: import pytorch as deeplearninglib
Box 2: ..DistributedSampler(Sampler)..
DistributedSampler(Sampler):
Sampler that restricts data loading to a subset of the dataset.
It is especially useful in conjunction with class:`torch.nn.parallel.DistributedDataParallel`. In such case, each process can pass a DistributedSampler instance as a DataLoader sampler, and load a subset of the original dataset that is exclusive to it.
Scenario: Sampling must guarantee mutual and collective exclusively between local and global segmentation models that share the same features.
Box 3: optimizer = deeplearninglib.train. GradientDescentOptimizer(learning_rate=0.10)
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