Deal of The Day! Hurry Up, Grab the Special Discount - Save 25% - Ends In 00:00:00 Coupon code: SAVE25
Welcome to Pass4Success

- Free Preparation Discussions
Mail Us support@pass4success.com
Location US
Mob_nav_barsMENU

Amazon MLS-C01 Exam - Topic 2 Question 132 Discussion

[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?
C) Use 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.
A) Load 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.
B) Use 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.
D) Use Amazon Lookout for Equipment to find and remove outliers from the dataset.

Amazon MLS-C01 Exam - Topic 2 Question 132 Discussion

Actual exam question for Amazon's MLS-C01 exam
Question #: 132
Topic #: 2
[All MLS-C01 Questions]

[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?

Show Suggested Answer Hide Answer
Suggested Answer: C

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

Limited Time Offer

25%

Off

Get Premium MLS-C01 Questions as Interactive Web-Based Practice Test or PDF

Contribute your Thoughts:

0/2000 characters
Submit Cancel
Raul
2 days ago
Option C sounds interesting with the anomaly detection visualization, but I wonder if it adds too much complexity for just removing outliers.
upvoted 0 times
...
Linn
7 days ago
I think using the bias report in option B could be useful, but I’m a bit unclear on how effective it is for outlier removal.
upvoted 0 times
...
Rodrigo
12 days ago
I remember we discussed using quartiles for outlier detection in class. Option A seems straightforward, but I'm not sure if it's the most efficient method.
upvoted 0 times
...

Save Cancel