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NEW QUESTION: 1
A fuser wrap condition occurs when the fuser detects the leading edge of the paper, but not the trailing edge. What is the mechanical cause of this condition?
A. Media does not reach the fuser.
B. The fuser sensors are not working.
C. Media wraps around or sticks to the fuser.
D. The fuser does not warm up in time.
Answer: B

NEW QUESTION: 2
회사는 소프트웨어 테스트에 사용되는 여러 랩 환경의 마이그레이션을 계획하고 있습니다. 각 실험실의 테스트 실행을 관리하기 위해 다양한 사용자 정의 툴링이 사용됩니다. 랩은 소프트웨어 테스트 실행에 불변 인프라를 사용하며 결과는 고 가용성 SQL 데이터베이스 클러스터에 저장됩니다. 사용자 정의 도구를 완전히 다시 작성하는 것은 마이그레이션 프로젝트의 범위를 벗어나지 만 마이그레이션 중에 워크로드를 최적화하려고 합니다.
어떤 응용 프로그램 마이그레이션 전략이이 요구 사항을 충족합니까?
A. 다시 호스트
B. 은퇴
C. 리 플랫폼
D. 리 팩터 / 리 아키텍처
Answer: C
Explanation:
https://aws.amazon.com/blogs/enterprise-strategy/6-strategies-for-migrating-applications-to-the-cloud/

NEW QUESTION: 3
Why do you need to split a machine learning dataset into training data and test data?
A. So you can try two different sets of features
B. To make sure your model is generalized for more than just the training data
C. So you can use one dataset for a wide model and one for a deep model
D. To allow you to create unit tests in your code
Answer: B
Explanation:
Explanation
The flaw with evaluating a predictive model on training data is that it does not inform you on how well the model has generalized to new unseen data. A model that is selected for its accuracy on the training dataset rather than its accuracy on an unseen test dataset is very likely to have lower accuracy on an unseen test dataset. The reason is that the model is not as generalized. It has specialized to the structure in the training dataset. This is called overfitting.
Reference: https://machinelearningmastery.com/a-simple-intuition-for-overfitting/