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NEW QUESTION: 1
都市の住宅販売データを含むデータセットがあります。データセットには、次の列が含まれています。
データセットの各行は、個々の住宅販売トランザクションに対応しています。
家の特徴に基づいて販売価格を予測するための最適なモデルを生成するには、自動機械学習を使用する必要があります。
どの値を使用す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：それぞれの正しい選択は1ポイントの価値があります。
Answer:
Explanation:
Explanation:
Box 1: Regression
Regression is a supervised machine learning technique used to predict numeric values.
Box 2: Price
Reference:
https://docs.microsoft.com/en-us/learn/modules/create-regression-model-azure-machine-learning-designer
NEW QUESTION: 2
Which three tasks can be performed by using the performance Schema?
A. Finding queries that are not using indexes
B. Finding rows that are locked by InnoDB
C. Finding the size of each table
D. Finding the part of a code in which a single query is spending time
E. Finding client connection attributes
Answer: A,B,E
NEW QUESTION: 3
A project manager has identified a minor skills gap in the operational team that will end up supporting the project solution.
Which of the following is the BEST risk mitigation strategy that the project manager should use?
A. Escalate this as an issue to the project control board and ensure that there is adequate discussion.
B. Organize adequate training and have one of the operational staff as part of the project team.
C. Raise a risk in the risk register, identify the likelihood and the consequence of the risk occurring.
D. Have the project adequately document the solution and ensure a transition is in place.
Answer: B
NEW QUESTION: 4
フォルダーを参照するcsvjolderという名前のファイルデータセットを登録します。フォルダーには、AzureストレージBLOBコンテナー内の複数のコンマ区切り値（CSV）ファイルが含まれています。次のコードを使用して、ファイルデータセットからデータをロードするスクリプトを実行する予定です。次の変数を作成してインスタンス化します。
次のコードがあります。
スクリプトが参照するファイルをスクリプトが確実に読み取れるようにするには、データセットを渡す必要があります。コードコメントを置き換えるには、どのコードセグメントを挿入する必要がありますか？
A）
B）
C）
D）
A. オプションC
B. オプションB
C. オプションD
D. オプションA
Answer: C
Explanation:
Explanation
Example:
from azureml.train.estimator import Estimator
script_params = {
# to mount files referenced by mnist dataset
'--data-folder': mnist_file_dataset.as_named_input('mnist_opendataset').as_mount(),
'--regularization': 0.5
}
est = Estimator(source_directory=script_folder,
script_params=script_params,
compute_target=compute_target,
environment_definition=env,
entry_script='train.py')
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/tutorial-train-models-with-aml