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NEW QUESTION: 1
Which objects are assigned to an Integrated Configuration Object? Note: There are 2 correct answers to this question.
A. XSLT Mapping
B. Communication Channel
C. Imported Archive
D. Operation Mapping
Answer: B,D
NEW QUESTION: 2
In an SAP S/4HANA environment, which elements need a direct connection to the BES system?
There are 2 correct answers to this question.
Response:
A. Analytical apps
B. Fact sheet apps
C. Legacy apps
D. SAP fiori search
Answer: C,D
NEW QUESTION: 3
Big Dataのコンサルティング会社は、請求とセキュリティ上の理由から、顧客の作業負荷を分けたいと考えています。同社は、これらのワークロードに対する請求およびセキュリティ管理を維持したいと考えています。
ベストプラクティスによると、共有リソースが不要な場合、ワークロードをどのように分離できますか。
A. AWSリージョンを各顧客専用にします。 Amazon Route 53の各エントリが一意であることを確認してください。
B. AWSの組織内で一括請求機能を指定してカスタマーアカウントを作成します。
C. 各顧客に自分のアカウントの作成を要求します。一括請求を受けるにはAWSサポートにお問い合わせください。
D. 顧客ごとに個別のVPCを作成します。セキュリティグループを使用してトラフィックを隔離します。
Answer: B
NEW QUESTION: 4
Azure Machine Learningワークスペースには、という名前のデータセットがあります。データセット内のデータのサンプルは次のとおりです。
自動機械学習を使用して、価格列を予測するための最適な回帰モデルを見つけたいと考えています。
Azure Machine Learning SDKを使用して、自動機械学習実験を構成する必要があります。
コード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、回答領域で適切なオプションを選択します。
注:正しい選択はそれぞれ1ポイントの価値があります。
Answer:
Explanation:
Explanation
Box 1: training_data
The training data to be used within the experiment. It should contain both training features and a label column (optionally a sample weights column). If training_data is specified, then the label_column_name parameter must also be specified.
Box 2: validation_data
Provide validation data: In this case, you can either start with a single data file and split it into training and validation sets or you can provide a separate data file for the validation set. Either way, the validation_data parameter in your AutoMLConfig object assigns which data to use as your validation set.
Example, the following code example explicitly defines which portion of the provided data in dataset to use for training and validation.
dataset = Dataset.Tabular.from_delimited_files(data)
training_data, validation_data = dataset.random_split(percentage=0.8, seed=1) automl_config = AutoMLConfig(compute_target = aml_remote_compute, task = 'classification', primary_metric = 'AUC_weighted', training_data = training_data, validation_data = validation_data, label_column_name = 'Class' ) Box 3: label_column_name label_column_name:
The name of the label column. If the input data is from a pandas.DataFrame which doesn't have column names, column indices can be used instead, expressed as integers.
This parameter is applicable to training_data and validation_data parameters.
Reference:
https://docs.microsoft.com/en-us/python/api/azureml-train-automl-client/azureml.train.automl.automlconfig.auto