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NEW QUESTION: 1
관리자는 Amazon Machine Learning 서비스를 사용하여 귀사를 언급하는 소셜 미디어 게시물을 응답이 필요한 게시물과 그렇지 않은 게시물로 분류합니다. 10,000 개의 게시물에 대한 교육 데이터 세트에는 타임 스탬프, 작성자 및 게시물 전문을 포함하여 각 게시물의 세부 정보가 들어 있습니다. 교육에 필요한 대상 레이블이 누락되었습니다.
유효한 대상 레이블 데이터를 생성하는 두 가지 옵션은 무엇입니까?
A. 두 클래스의 선험적 확률 분포를 사용하여 Monte-Carlo 시뮬레이션을 사용하여 레이블을 생성합니다.
B. Amazon Mechanical Mechanical 웹 서비스를 사용하여 Turk 작업자에게 게시물에 레이블을 달라고 요청하는 Human Intelligence Tasks를 게시합니다.
C. 정서 분석 NLP 라이브러리를 사용하여 게시물에 응답이 필요한지 여부를 결정합니다.
D. 소셜 미디어 담당 팀에게 각 게시물을 검토하고 라벨을 제공하도록 요청하십시오.
Answer: B,D
Explanation:
You need accurate data to train the service and get accurate results from future data. The options described in B and D would end up training an ML model using the output from a different machine learning model and therefore would significantly increase the possible error rate. It is extremely important to have a very low error rate (if any!) in your training set, and therefore human-validated or assured labels are essential.
It is essential when writing mobile applications that you consider the security of both how the application

NEW QUESTION: 2
Your network contains an Active Directory domain. The domain contains a computer named Computer1 that runs Windows 10.
The domain contains the users shown in the following table.

Computer1 has the local users shown in the following table.

All users have Microsoft accounts.
Which two users can be configured to sign in by using their Microsoft account? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
A. User4
B. User3
C. User2
D. User1
E. User5
Answer: A,E

NEW QUESTION: 3
The microservice engine provides gray-scale publishing between microservices, and supports (Such as Header).
A. True
B. False
Answer: A