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NEW QUESTION: 1
DRAG DROP
Answer:
Explanation:
Explanation:
NEW QUESTION: 2
CloudFormation 스택의 리소스 중 하나를 만들 수 없는 경우 기본적으로 어떻게 됩니까?
A. 이전에 생성 된 리소스가 삭제되고 스택 생성이 종료됩니다.
B. CloudFormation 템플릿이 미리 구문 분석되어 스택 생성이 성공합니다.
C. 스택 생성이 계속되고 최종 결과는 실패한 단계를 나타냅니다.
D. 이전에 생성 된 리소스는 유지되지만 스택 생성은 종료됩니다.
Answer: A
Explanation:
https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/stacks.html
AWS CloudFormation ensures all stack resources are created or deleted as appropriate. Because AWS CloudFormation treats the stack resources as a single unit, they must all be created or deleted successfully for the stack to be created or deleted. If a resource cannot be created, AWS CloudFormation rolls the stack back and automatically deletes any resources that were created. If a resource cannot be deleted, any remaining resources are retained until the stack can be successfully deleted.
NEW QUESTION: 3
You are developing a linear regression model in Azure Machine Learning Studio. You run an experiment to compare different algorithms.
The following image displays the results dataset output:
Use the drop-down menus to select the answer choice that answers each question based on the information presented in the image.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Boosted Decision Tree Regression
Mean absolute error (MAE) measures how close the predictions are to the actual outcomes; thus, a lower score is better.
Box 2:
Online Gradient Descent: If you want the algorithm to find the best parameters for you, set Create trainer mode option to Parameter Range. You can then specify multiple values for the algorithm to try.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/evaluate-model
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/linear-regression