Amazon MLS-C01 Exam - Topic 2 Question 132 Discussion

Actual exam question for Amazon's MLS-C01 exam

Question #: 132
Topic #: 2

[Exploratory Data Analysis]

A company uses sensors on devices such as motor engines and factory machines to measure parameters, temperature and pressure. The company wants to use the sensor data to predict equipment malfunctions and reduce services outages.

The Machine learning (ML) specialist needs to gather the sensors data to train a model to predict device malfunctions The ML spoctafst must ensure that the data does not contain outliers before training the ..el.

What can the ML specialist meet these requirements with the LEAST operational overhead?

ALoad the data into an Amazon SagcMaker Studio notebook. Calculate the first and third quartile Use a SageMaker Data Wrangler data (low to remove only values that are outside of those quartiles.

BUse an Amazon SageMaker Data Wrangler bias report to find outliers in the dataset Use a Data Wrangler data flow to remove outliers based on the bias report.

CUse an Amazon SageMaker Data Wrangler anomaly detection visualization to find outliers in the dataset. Add a transformation to a Data Wrangler data flow to remove outliers.

DUse Amazon Lookout for Equipment to find and remove outliers from the dataset.

Show Suggested Answer

Suggested Answer: C

by Marylin at May 30, 2026, 07:35 AM

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