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NEW QUESTION: 1
Which of the following is the most effective control to prevent unauthorized entrance of a former employee of the organization?
A. Revoking the former employee's biometrics from the entrance systems
B. Installing multiple high-powered surveillance cameras throughout the organization
C. Installing security guards who have undergone a background check at all entrances.
D. Keeping doors locked and accessible with a key that is provided only to employees
Answer: A
NEW QUESTION: 2
Which of the following about the description of Huawei SmartLogger accessing third-party devices is correct? (Multiple Choice)
A. Access to third-party devices that support the standard Modbus-RTU protocol
B. Custom devices do not support automatic search and need to be added manually
C. Because the agreement information points of each manufacturer are inconsistent, you need to configure the communication point table file.
D. Custom devices support automatic search, no need to manually add
Answer: A,B,C
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