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Exam AWS Certified Machine Learning Engineer - Associate MLA-C01 All Questions

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Exam AWS Certified Machine Learning Engineer - Associate MLA-C01 topic 1 question 75 discussion

Exam question from Amazon's AWS Certified Machine Learning Engineer - Associate MLA-C01
Question #: 75
Topic #: 1
[All AWS Certified Machine Learning Engineer - Associate MLA-C01 Questions]

A company wants to develop an ML model by using tabular data from its customers. The data contains meaningful ordered features with sensitive information that should not be discarded. An ML engineer must ensure that the sensitive data is masked before another team starts to build the model.
Which solution will meet these requirements?

  • A. Use Amazon Made to categorize the sensitive data.
  • B. Prepare the data by using AWS Glue DataBrew.
  • C. Run an AWS Batch job to change the sensitive data to random values.
  • D. Run an Amazon EMR job to change the sensitive data to random values.
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Suggested Answer: B 🗳️
by GiorgioGss at Nov. 28, 2024, 5:23 p.m.
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ZoroRoronoa
2 months ago
Selected Answer: B
AWS Glue DataBrew (Option B) is the most efficient and user-friendly solution for masking sensitive information while retaining the structure and order of tabular data, making it ideal for preparing data for ML model development. AWS Macie cannot mask data.
upvoted 3 times
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wizardmo
2 months, 3 weeks ago
Selected Answer: A
question error made -> macie
upvoted 3 times
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Saransundar
2 months, 4 weeks ago
Selected Answer: B
Customer tabular data → AWS Glue DataBrew → Mask sensitive data → Prepare for ML model building
upvoted 2 times
...
GiorgioGss
3 months ago
Selected Answer: B
https://docs.aws.amazon.com/databrew/latest/dg/personal-information-protection.html
upvoted 3 times
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