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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 25 discussion

Exam question from Amazon's AWS Certified Machine Learning Engineer - Associate MLA-C01
Question #: 25
Topic #: 1
[All AWS Certified Machine Learning Engineer - Associate MLA-C01 Questions]

A company uses Amazon Athena to query a dataset in Amazon S3. The dataset has a target variable that the company wants to predict.
The company needs to use the dataset in a solution to determine if a model can predict the target variable.
Which solution will provide this information with the LEAST development effort?

  • A. Create a new model by using Amazon SageMaker Autopilot. Report the model's achieved performance.
  • B. Implement custom scripts to perform data pre-processing, multiple linear regression, and performance evaluation. Run the scripts on Amazon EC2 instances.
  • C. Configure Amazon Macie to analyze the dataset and to create a model. Report the model's achieved performance.
  • D. Select a model from Amazon Bedrock. Tune the model with the data. Report the model's achieved performance.
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Suggested Answer: A 🗳️
by GiorgioGss at Nov. 27, 2024, 9:16 p.m.
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Sadrik
4 days, 21 hours ago
Selected Answer: A
Amazon Bedrock provides foundation models (LLMs) for tasks like text generation but is not used for structured data prediction.
upvoted 1 times
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Sid4ops
2 weeks, 2 days ago
Selected Answer: A
Best answere
upvoted 1 times
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chris_spencer
3 weeks, 3 days ago
Selected Answer: A
A is the most logical answer. B. There is too much effort to set up those scripts and EC2. C. Macie does not fit this use case. D. Lots of effort to set up bedrock for this purpose.
upvoted 2 times
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