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Certified Professional Coder (CPC) Exam

  • Exam Number/Code : CPC
  • Exam Name : Certified Professional Coder (CPC) Exam
  • Questions and Answers : 213 Q&As
  • Update Time: 2019-01-10
  • Price: $ 99.00 $ 39.00
CPC

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NEW QUESTION: 1
What is the MOST common component of a vulnerability management framework?
A. Threat analysis
B. Backup management
C. Risk analysis
D. Patch management
Answer: D
Explanation:
Reference: https://www.helpnetsecurity.com/2016/10/11/effective-vulnerability-management-process/

NEW QUESTION: 2
A Windows desktop PC user states that they have sent several print jobs to their locally connected printer, yet none have printed. The printer has no error conditions on the control panel. Which of the following should the technician do FIRST in troubleshooting this problem?
A. Open the printer properties page and send a test print to it.
B. Power the printer off and on and send one test document to it.
C. Clear the print queue of all documents and resend one to test the printer.
D. Check if Use Printer Offline has been selected.
Answer: D

NEW QUESTION: 3
You are designing a solution for a company. The solution will use model training for objective classification.
You need to design the solution.
What should you recommend?
A. a Spark application that uses Spark MLib.
B. an Azure Cognitive Services application
C. a Spark Streaming job
D. Power BI models
E. interactive Spark queries
Answer: A
Explanation:
Explanation
Spark in SQL Server big data cluster enables AI and machine learning.
You can use Apache Spark MLlib to create a machine learning application to do simple predictive analysis on an open dataset.
MLlib is a core Spark library that provides many utilities useful for machine learning tasks, including utilities that are suitable for:
* Classification
* Regression
* Clustering
* Topic modeling
* Singular value decomposition (SVD) and principal component analysis (PCA)
* Hypothesis testing and calculating sample statistics
References:
https://docs.microsoft.com/en-us/azure/hdinsight/spark/apache-spark-machine-learning-mllib-ipython