A company has developed an ML model to predict real estate sale prices. The company wants to deploy the model to make predictions without managing servers or infrastructure.
Which solution meets these requirements?
A.
Deploy the model on an Amazon EC2 instance.
B.
Deploy the model on an Amazon Elastic Kubernetes Service (Amazon EKS) cluster.
C.
Deploy the model by using Amazon CloudFront with an Amazon S3 integration.
D.
Deploy the model by using an Amazon SageMaker endpoint.
D. Deploy the model by using an Amazon SageMaker endpoint.
Explanation:
Amazon SageMaker is a fully managed service that enables you to quickly build, train, and deploy machine learning models at scale. Deploying a model using an Amazon SageMaker endpoint allows the company to make predictions without needing to manage servers or infrastructure. SageMaker automatically handles the provisioning of resources, scaling, and maintenance, making it an ideal solution for production-grade ML deployments.
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Jessiii
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2 months agoaws_Tamilan
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