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NEW QUESTION: 1
You administer client computers that have Windows 7 Enterprise installed.
A server named Server1 has an IP address of 10.10.4.56. The server accepts Remote Desktop connections at a custom port 10876.
You need to connect to the server from a client computer by using Remote Desktop.
What should you do?
A. From the Advanced tab of your Remote Desktop connection, configure the IP address and port of Server1 as the RD Gateway Server.
B. From an elevated command prompt, run mstsc.exe /v:Server1:10876.
C. From an elevated command prompt, run mstsc.exe Server1 port:10876.
D. From an elevated command prompt, run mstsc.exe 10.10.4.56 port: 10876.
Answer: B
Explanation:
Explanation/Reference:
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NEW QUESTION: 2
HOTSPOT
You need to implement the map of the runners' paths.
How should you build the video viewer? (To answer, select the appropriate options in the answer area.)


Answer:
Explanation:

NEW QUESTION: 3
인적 검토는 비용이 많이 들고 오류가 발생하기 쉬우므로 보험 회사는 청구 준수 검토를 자동화해야 합니다. 회사에는 많은 클레임 세트와 각각에 대한 규정 준수 레이블이 있습니다.
각 주장은 영어로 된 몇 개의 문장으로 구성되며 그 중 대부분은 복잡한 관련 정보를 포함합니다. 경영진은 Amazon SageMaker 내장 알고리즘을 사용하여 각 클레임을 읽고 클레임이 규정을 준수하는지 예측하도록 훈련 할 수 있는 기계 학습 감독 모델을 설계하려고 합니다.
다운 스트림 감독 작업의 입력으로 사용할 클레임에서 특징을 추출하려면 어떤 접근 방식을 사용해야 합니까?
A. 분류 모드에서 Amazon SageMaker BlazingText를 교육 세트의 레이블이 지정된 클레임에 적용하여 각각 준수 및 비준수 레이블에 해당하는 클레임에 대한 기능을 도출합니다.
B. 전체 데이터 세트의 클레임에서 토큰 사전을 가져옵니다. 학습 세트의 각 클레임에서 찾은 토큰에 원-핫 인코딩을 적용합니다. 파생 된 기능 공간을 Amazon SageMaker 내장지도 학습 알고리즘에 대한 입력으로 보냅니다.
C. Word2Vec 모드의 Amazon SageMaker BlazingText를 교육 세트의 클레임에 적용합니다. 파생 된 기능 공간을 다운 스트림 감독 작업에 대한 입력으로 보냅니다.
D. Amazon SageMaker Object2Vec을 교육 세트의 클레임에 적용합니다. 파생 된 기능 공간을 다운 스트림 감독 작업에 대한 입력으로 보냅니다.
Answer: D
Explanation:
Amazon SageMaker Object2Vec generalizes the Word2Vec embedding technique for words to more complex objects, such as sentences and paragraphs. Since the supervised learning task is at the level of whole claims, for which there are labels, and no labels are available at the word level, Object2Vec needs be used instead of Word2Vec.