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NEW QUESTION: 1
A da element is an example of
A. Technical Domain
B. Physical Definition
C. Semantic Domain
D. Business Object
Answer: C
NEW QUESTION: 2
재무 기간이 끝나면 Flowers for Me의 회계사인 Melanie는 손익 계산서 예산 보고서를 발행합니다. 그녀는 회사가 예산에서 벗어나고 있다는 사실에 놀랐습니다. 예산 편차의 원인은 무엇입니까?
정답을 선택하십시오.
응답:
A. 회사의 예산을 설정할 때 모든 지출 계정을 예산 계정으로 표시했습니다.
B. 연중 예산 예산 편차는 주 예산 시나리오와 다른 예산 시나리오에 따라 수행되었습니다.
C. Melanie는 G / L 계정이 예산을 초과하는 경우 예산 편차를 확인할 권한이 없습니다.
D. Melanie는 주 예산 시나리오와 다른 금액의 예산 시나리오에 따라 보고서를 발행했습니다.
Answer: D
NEW QUESTION: 3
You administer a Microsoft SQL Server database. The database contains a Product table created by using the following definition:
You need to ensure that the minimum amount of disk space is used to store the data in the Product table.
What should you do?
A. Implement row-level compression.
B. Implement Unicode Compression.
C. Implement page-level compression.
D. Convert all indexes to Column Store indexes.
Answer: C
Explanation:
Explanation/Reference:
Reference: http://msdn.microsoft.com/en-us/library/cc280449.aspx
Reference: http://msdn.microsoft.com/en-us/library/cc280464.aspx
Reference: http://msdn.microsoft.com/en-us/library/cc280576.aspx
Reference: http://msdn.microsoft.com/en-us/library/ee240835.aspx
NEW QUESTION: 4
PyTorch深層学習フレームワークを使用するマルチクラス画像分類深層学習モデルを作成します。
分類モデルのハイパーパラメーターを最適化するには、Azure Machine Learningハイパードライブを構成する必要があります。
精度が最も高いモデルとなるハイパーパラメーター値を決定するには、プライマリメトリックを定義する必要があります。
どの3つのアクションを実行する必要がありますか？それぞれの正解がソリューションの一部を示しています。
注：それぞれの正しい選択は1ポイントの価値があります。
A. bird_classifier_train.pyスクリプトを実行して最大化するために使用される推定器のprimary_metric_goalを設定します。
B. bird_classifier_train.pyスクリプトにコードを追加して、モデルの検証損失を計算し、キー損失のある浮動小数点値としてログに記録します。
C. bird_classifier_train.pyスクリプトの実行に使用される推定器のprimary_metric_nameをlossに設定します。
D. bird_classifier_train.pyスクリプトを実行するために使用される推定器のprimary_metric_nameを正確に設定します。
E. 最小化するためにbird_classifier_train.pyスクリプトを実行するために使用される推定器のprimary_metric_goalを設定します。
F. bird_classifier_train.pyスクリプトにコードを追加して、モデルの検証精度を計算し、それをキー精度の浮動小数点値として記録します。
Answer: A,D,F
Explanation:
Explanation
AD:
primary_metric_name="accuracy",
primary_metric_goal=PrimaryMetricGoal.MAXIMIZE
Optimize the runs to maximize "accuracy". Make sure to log this value in your training script.
Note:
primary_metric_name: The name of the primary metric to optimize. The name of the primary metric needs to exactly match the name of the metric logged by the training script.
primary_metric_goal: It can be either PrimaryMetricGoal.MAXIMIZE or PrimaryMetricGoal.MINIMIZE and determines whether the primary metric will be maximized or minimized when evaluating the runs.
F: The training script calculates the val_accuracy and logs it as "accuracy", which is used as the primary metric.