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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 56 discussion

An ML engineer needs to use Amazon SageMaker to fine-tune a large language model (LLM) for text summarization. The ML engineer must follow a low-code no-code (LCNC) approach.
Which solution will meet these requirements?

  • A. Use SageMaker Studio to fine-tune an LLM that is deployed on Amazon EC2 instances.
  • B. Use SageMaker Autopilot to fine-tune an LLM that is deployed by a custom API endpoint.
  • C. Use SageMaker Autopilot to fine-tune an LLM that is deployed on Amazon EC2 instances.
  • D. Use SageMaker Autopilot to fine-tune an LLM that is deployed by SageMaker JumpStart.
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Suggested Answer: D 🗳️

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Saransundar
1 month, 2 weeks ago
Selected Answer: D
LCNC solution: SageMaker Autopilot → SageMaker JumpStart → Deploy pre-trained LLM → Fine-tune for text summarization
upvoted 1 times
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GiorgioGss
1 month, 3 weeks ago
Selected Answer: D
https://d1.awsstatic.com/events/Summits/reinvent2023/AIM217_Democratize-ML-with-no-code-low-code-using-Amazon-SageMaker-Canvas.pdf
upvoted 1 times
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