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NEW QUESTION: 1
HOTSPOT
You have an Azure virtual network named VNet1 that connects to your on-premises network by using a site-to-site VPN. VNet1 contains one subnet named Subnet1.
Subnet1 is associated to a network security group (NSG) named NSG1. Subnetl1contains a basic internal load balancer named IIB1. II B1 has three Azure virtual machines in the backend pod You need to cottec1 data about the IP addresses that connects to ILB1. You must be able to run interactive queries from the Azure portal against the collected data.
What should you do? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION: 2
You have suggested to a customer that a Data Deduplication Assessment A (DDA:A) would help them evaluate deduplication in their environment. What would you recommend after the completion of the DDA:A scan?
A. Schedule and run a File System Assessment
B. Map drives for the DDA:B scan
C. Perform the DDA:A backup script
D. Rerun the DDA:A scan within one week of the first scan
Answer: A
NEW QUESTION: 3
機械学習モデルを使用してインテリジェントなソリューションを構築しています。
環境は次の要件をサポートする必要があります。
*データサイエンティストはクラウド環境でノートブックを構築する必要がある
*データサイエンティストは、機械学習パイプラインで自動フィーチャエンジニアリングとモデル構築を使用する必要があります。
*動的なワーカー割り当てでSparkインスタンスを使用して再トレーニングするには、ノートブックを展開する必要があります。
*ノートブックは、ローカルでバージョン管理するためにエクスポート可能である必要があります。
環境を作成する必要があります。
どの4つのアクションを順番に実行する必要がありますか？回答するには、適切なアクションをアクションのリストから回答エリアに移動し、正しい順序に並べます。
Answer:
Explanation:
Explanation
Step 1: Create an Azure HDInsight cluster to include the Apache Spark Mlib library Step 2: Install Microsot Machine Learning for Apache Spark You install AzureML on your Azure HDInsight cluster.
Microsoft Machine Learning for Apache Spark (MMLSpark) provides a number of deep learning and data science tools for Apache Spark, including seamless integration of Spark Machine Learning pipelines with Microsoft Cognitive Toolkit (CNTK) and OpenCV, enabling you to quickly create powerful, highly-scalable predictive and analytical models for large image and text datasets.
Step 3: Create and execute the Zeppelin notebooks on the cluster
Step 4: When the cluster is ready, export Zeppelin notebooks to a local environment.
Notebooks must be exportable to be version controlled locally.
References:
https://docs.microsoft.com/en-us/azure/hdinsight/spark/apache-spark-zeppelin-notebook
https://azuremlbuild.blob.core.windows.net/pysparkapi/intro.html