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NEW QUESTION: 1
How frequently should business contingency procedures be tested and updated?
A. quarterly tests I updates as needed
B. at least every second year
C. half-yearly tests / yearly updates
D. at least yearly
Answer: D

NEW QUESTION: 2
If a table named MY_TAB contains 100 rows and the following statement is executed:

What will happen?
A. The statement will fail because a subquery cannot be used with a DELETE statement.
B. The statement will fail because a table name was not specified with the DELETE statement.
C. The first 5 rows in the table will be deleted.
D. The last 5 rows in the table will be deleted.
Answer: D

NEW QUESTION: 3
Azure Machine Learningのハイパードライブ機能を使用して、モデルをトレーニングするときに最適なハイパーパラメーター値を決定することを計画しています。
次のハイパーパラメータ値の組み合わせを試すには、ハイパードライブを使用する必要があります。早期終了ポリシーを適用してはなりません。
Learning_rate:0.001〜0.1の任意の値
* batch_size:16、32、または64
ハイパードライブ実験のサンプリング方法を構成する必要がありますどの2つのサンプリング方法を使用できますか?それぞれの正解は完全な解決策です。
注:正しい選択はそれぞれ1ポイントの価値があります。
A. ベイジアンサンプリング
B. ランダムサンプリング
C. グリッドサンプリング
D. サンプリングなし
Answer: A,B
Explanation:
Explanation
C: Bayesian sampling is based on the Bayesian optimization algorithm and makes intelligent choices on the hyperparameter values to sample next. It picks the sample based on how the previous samples performed, such that the new sample improves the reported primary metric.
Bayesian sampling does not support any early termination policy
Example:
from azureml.train.hyperdrive import BayesianParameterSampling
from azureml.train.hyperdrive import uniform, choice
param_sampling = BayesianParameterSampling( {
"learning_rate": uniform(0.05, 0.1),
"batch_size": choice(16, 32, 64, 128)
}
)
D: 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.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters

NEW QUESTION: 4
企業は、ネットワーク、IAMポリシー、および複数の3層アプリケーションで構成される複雑なシステムを使用しています。新しいシステムの要件はまだ定義されているため、最終設計に存在するAWSコンポーネントの数は不明です。 DevOpsエンジニアは、AWS CloudFormationを使用してAWSリソースの定義を開始し、新しいインフラストラクチャを自動化してバージョン管理する必要があります。
CloudFormationを使用して新しい環境を作成するためのベストプラクティスは何ですか?
A. Amazon VPCを使用してネットワーク層を手動で構築し、CloudFormationを使用して他のすべてのリソースを定義します。
B. システムに必要なすべてのリソースを含む単一のテンプレートを作成して、バージョン管理するテンプレートが1つだけになるようにします。
C. システムの論理部分ごとに複数の個別のテンプレートを作成し、CloudFormationでクロススタック参照を使用し、バージョン管理でいくつかのテンプレートを維持します。
D. システムの論理部分ごとに多数の個別のテンプレートを作成し、SDKを実行するAmazon EC2インスタンスを使用してきめ細かな制御を行い、出力を提供します。
Answer: C