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MLS-C01 · Question #207

MLS-C01 Question #207: Real Exam Question with Answer & Explanation

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Modeling

Question

A real-estate company is launching a new product that predicts the prices of new houses. The historical data for the properties and prices is stored in .csv format in an Amazon S3 bucket. The data has a header, some categorical fields, and some missing values. The company's data scientists have used Python with a common open-source library to fill the missing values with zeros. The data scientists have dropped all of the categorical fields and have trained a model by using the open-source linear regression algorithm with the default parameters. The accuracy of the predictions with the current model is below 50%. The company wants to improve the model performance and launch the new product as soon as possible. Which solution will meet these requirements with the LEAST operational overhead?

Options

  • ACreate a service-linked role for Amazon Elastic Container Service (Amazon ECS) with
  • BCreate an Amazon SageMaker notebook with a new IAM role that is associated with the
  • CCreate an IAM role with access to Amazon S3, Amazon SageMaker, and AWS Lambda.
  • DCreate an IAM role for Amazon SageMaker with access to the S3 bucket. Create a

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Topics

#Amazon SageMaker#Model Improvement#Operational Efficiency#Feature Engineering
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