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Exam AWS Certified AI Practitioner AIF-C01 topic 1 question 111 discussion

Exam question from Amazon's AWS Certified AI Practitioner AIF-C01
Question #: 111
Topic #: 1
[All AWS Certified AI Practitioner AIF-C01 Questions]

A financial institution is building an AI solution to make loan approval decisions by using a foundation model (FM). For security and audit purposes, the company needs the AI solution's decisions to be explainable.

Which factor relates to the explainability of the AI solution's decisions?

  • A. Model complexity
  • B. Training time
  • C. Number of hyperparameters
  • D. Deployment time
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Suggested Answer: A 🗳️
by 26b8fe1 at Dec. 26, 2024, 3:55 p.m.
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Jessiii
2 weeks, 6 days ago
Selected Answer: A
More complex models are harder to interpret; simpler models improve explainability.
upvoted 1 times
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may2021_r
2 months ago
Selected Answer: A
The correct answer is A. Model complexity directly affects how interpretable and explainable AI decisions are.
upvoted 1 times
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aws_Tamilan
2 months ago
Selected Answer: A
Model complexity is the most important factor when considering the explainability of the AI solution's decisions, as simpler models with fewer parameters and layers are typically easier to explain and interpret.
upvoted 3 times
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26b8fe1
2 months, 1 week ago
Selected Answer: A
Model complexity in machine learning refers to the capacity of a model to capture and represent patterns in the data. It involves the depth, breadth, and intricacy of the underlying structure of the model. Here are some key aspects
upvoted 1 times
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