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最新的 AWS Certified Associate MLA-C01 免費考試真題:

1. An ML engineer has an Amazon Comprehend custom model in Account A in the us-east-1 Region. The ML engineer needs to copy the model to Account # in the same Region.
Which solution will meet this requirement with the LEAST development effort?

A) Create a resource-based IAM policy. Use the Amazon Comprehend ImportModel API operation to copy the model to Account B.
B) Create an AWS Site-to-Site VPN connection between Account A and Account # to transfer the model.
C) Use AWS DataSync to replicate the model from Account A to Account B.
D) Use Amazon S3 to make a copy of the model. Transfer the copy to Account B.

2. A company is planning to use Amazon SageMaker to make classification ratings that are based on images.
The company has 6 ## of training data that is stored on an Amazon FSx for NetApp ONTAP system virtual machine (SVM). The SVM is in the same VPC as SageMaker.
An ML engineer must make the training data accessible for ML models that are in the SageMaker environment.
Which solution will meet these requirements?

A) Create a catalog connection from SageMaker Data Wrangler to the FSx for ONTAP file system.
B) Create a direct connection from SageMaker Data Wrangler to the FSx for ONTAP file system.
C) Create an Amazon S3 bucket. Use Mountpoint for Amazon S3 to link the S3 bucket to the FSx for ONTAP file system.
D) Mount the FSx for ONTAP file system as a volume to the SageMaker Instance.

3. An ML engineer needs to use AWS CloudFormation to create an ML model that an Amazon SageMaker endpoint will host.
Which resource should the ML engineer declare in the CloudFormation template to meet this requirement?

A) AWS::SageMaker::Endpoint
B) AWS::SageMaker::Pipeline
C) AWS::SageMaker::Model
D) AWS::SageMaker::NotebookInstance

4. An ML engineer needs to use an ML model to predict the price of apartments in a specific location.
Which metric should the ML engineer use to evaluate the model's performance?

A) F1 score
B) Accuracy
C) Area Under the ROC Curve (AUC)
D) Mean absolute error (MAE)

5. A credit card company has a fraud detection model in production on an Amazon SageMaker endpoint. The company develops a new version of the model. The company needs to assess the new model's performance by using live data and without affecting production end users.
Which solution will meet these requirements?

A) Set up SageMaker Debugger and create a custom rule.
B) Set up blue/green deployments with canary traffic shifting.
C) Set up shadow testing with a shadow variant of the new model.
D) Set up blue/green deployments with all-at-once traffic shifting.

問題與答案：