Question 12 of 68
Single answerCertylQ Case study - An ML engineer is developing a fraud detection model on AWS. The training dataset includes transaction logs, customer profiles, and tables from an on-premises MySQL database.The transaction logs and customer profiles are stored in Amazon S3. features have interdependencies. The algorithm is not capturing all the desired undlerlying patterns in the data. dataset to maximize the accuracy of the model. Which action will meet this requirement with the LEAST operational overhead?
AUse AWS Glue to transform the categorical data into numerical data.
BUse AWS Glue to transform the numerical data into categorical data.
✓CUse Amazon SageMaker Data Wrangler to transform the categorical data into numerical data.
DUse Amazon SageMaker Data Wrangler to transform the numerical data into categorical data.
✓
Correct Answer: C
Use Amazon SageMaker Data Wrangler to transform the categorical data into numerical data.
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Explanation
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