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Total Questions : 241 With In-Depth Explanation
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Last Update June 5, 2026
Total Questions : 241 With In-Depth Explanation
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Last Update June 5, 2026
Total Questions : 241
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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.
The dataset has a class imbalance that affects the learning of the model ' s algorithm. Additionally, many of the features have interdependencies. The algorithm is not capturing all the desired underlying patterns in the data.
The ML engineer needs to use an Amazon SageMaker built-in algorithm to train the model.
Which algorithm should the ML engineer use to meet this requirement?
TESTED 05 Jun 2026
