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NEW QUESTION: 1
デザイナーを使用して新しいAzure Machine Learningパイプラインを作成しています。
パイプラインは、Webサイトで公開されているコンマ区切り値（CSV）ファイルのデータを使用してモデルをトレーニングする必要があります。このファイルのデータセットを作成していません。
最小限の管理作業で、CSVファイルからデザイナーパイプラインにデータを取り込む必要があります。
Designerのどのモジュールをパイプラインに追加する必要がありますか？
A. データセット
B. データのインポート
C. データを手動で入力します
D
D. CSVに変換
Answer: A
Explanation:
The preferred way to provide data to a pipeline is a Dataset object. The Dataset object points to data that lives in or is accessible from a datastore or at a Web URL. The Dataset class is abstract, so you will create an instance of either a FileDataset (referring to one or more files) or a TabularDataset that's created by from one or more files with delimited columns of data.
Example:
from azureml.core import Dataset
iris_tabular_dataset = Dataset.Tabular.from_delimited_files([(def_blob_store, 'train-dataset/iris.csv')]) Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-create-your-first-pipeline

NEW QUESTION: 2
Refer to the exhibit.

Refer to the exhibit. Which switch in this configuration becomes the root bridge?
A. SW4
B. SW3
C. SW2
D. SW1
Answer: B

NEW QUESTION: 3
組織には、次のデータタイプとアクセスパターンを処理するデータストアが必要です。
*ファセット
* 探す
*柔軟なスキーマ（JSON）および固定スキーマ
*ノイズワードの除去
組織はどのデータストアを選択する必要がありますか？
A. Amazon DynamoDB
B. Amazon Elasticsearch Service
C. Amazon Redshift
D. Amazon Relational Database Service（RDS）
Answer: B