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NEW QUESTION: 1
Examine the exhibit to view the parameters set in your parameter file. You restart the instance.
To what value will the MEMORY_MAX_TARGET parameter be set by default?
Exhibit:

A. 600M
B. 320M
C. 120M
D. 440M
Answer: A

NEW QUESTION: 2
戦略的目標に対する情報セキュリティプログラムのパフォーマンスに関する有意義な情報を経営陣に提供するための最良の方法は次のうちどれですか？
A. バランススコアカードダッシュボードを確立します。
B. セキュリティ標準への準拠を示すために定期的なレポートを発行します。
C. 組織全体に情報セキュリティ戦略を公開します。
D. 情報セキュリティヒートマップを作成します。
Answer: A

NEW QUESTION: 3
Azure Machine Learning Serviceを使用して、ニューラルネットワーク分類モデルのハイパーパラメーター探索を自動化しています。
次の要件に従ってランダムサンプリングを使用してハイパーパラメーターを自動的に調整するには、ハイパーパラメーター空間を定義する必要があります。
*学習率は、平均値が10、標準偏差が3の正規分布から選択する必要があります。
*バッチサイズは16、32、64でなければなりません。
*維持確率は、0.05から0.1の範囲の均一な分布から選択された値でなければなりません。
Azure Machine Learning ServiceのPython APIのparam_samplingメソッドを使用する必要があります。
コードセグメントをどのように完成させる必要がありますか？ 回答するには、回答エリアで適切なオプションを選択します。
注：それぞれの正しい選択には1ポイントの価値があります。

Answer:
Explanation:

Explanation

In random sampling, hyperparameter values are randomly selected from the defined search space. Random sampling allows the search space to include both discrete and continuous hyperparameters.
Example:
from azureml.train.hyperdrive import RandomParameterSampling
param_sampling = RandomParameterSampling( {
"learning_rate": normal(10, 3),
"keep_probability": uniform(0.05, 0.1),
"batch_size": choice(16, 32, 64)
}
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-tune-hyperparameters

NEW QUESTION: 4
Which following statements about the four-step QoS process (classification, queuing, scheduling, and marking/remarking) executed for every packet entering a Nokia 7750 SR is TRUE?
A. Marking/remarking the packets will occur right after classification of the packet.
B. The process happens only before the packet goes through the switching fabric.
C. The process happens only before the packet goes onto the egress port.
D. Marking/remarking the packets is for future classification.
Answer: A