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NEW QUESTION: 1
다음 중 IS 감사인이 감사 후속 활동을 시작하기 전에 준비해야 하는 것은 무엇입니까?
A. 위험 측면에서 차이와 권장 사항이 표시된 히트 맵
B. 실행 계획에 포함 된 활동에 사용할 수 있는 리소스
C. 확정 된 구현 날짜와 함께 최종 보고서의 경영진 응답
D. 감사 보고서에 언급 된 차이 및 권장 사항에 대한 증거를 뒷받침 합니다.
Answer: C
NEW QUESTION: 2
A. Option B
B. Option D
C. Option A
D. Option C
Answer: B
NEW QUESTION: 3
You are building an intelligent solution using machine learning models.
The environment must support the following requirements:
* Data scientists must build notebooks in a cloud environment
* Data scientists must use automatic feature engineering and model building in machine learning pipelines.
* Notebooks must be deployed to retrain using Spark instances with dynamic worker allocation.
* Notebooks must be exportable to be version controlled locally.
You need to create the environment.
Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
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
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