MLS-C01 · Question #334
MLS-C01 Question #334: Real Exam Question with Answer & Explanation
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Question
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. Machine learning (ML) specialist needs to gather the sensors data to train a model to predict device malfunctions. The ML specialist must ensure that the data does not contain outliers before training the model. How can the ML specialist meet these requirements with the LEAST operational overhead?
Options
- ALoad the data into an Amazon SageMaker Studio notebook. Calculate the first and third quartile.
- BUse an Amazon SageMaker Data Wrangler bias report to find outliers in the dataset. Use a Data
- CUse an Amazon SageMaker Data Wrangler anomaly detection visualization to find outliers in the
- DUse Amazon Lookout for Equipment to find and remove outliers from the dataset.
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