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

Exam question from Amazon's AWS Certified AI Practitioner AIF-C01

Question #: 1
Topic #: 1

[All AWS Certified AI Practitioner AIF-C01 Questions]

A company makes forecasts each quarter to decide how to optimize operations to meet expected demand. The company uses ML models to make these forecasts.
An AI practitioner is writing a report about the trained ML models to provide transparency and explainability to company stakeholders.
What should the AI practitioner include in the report to meet the transparency and explainability requirements?

A. Code for model training
B. Partial dependence plots (PDPs)
C. Sample data for training
D. Model convergence tables

Show Suggested Answer

Suggested Answer: B 🗳️

by p2pcerts at Nov. 3, 2024, 8:52 a.m.

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sultanyousaf283

Highly Voted 1 week, 6 days ago

The AWS Certified AI Practitioner (AIF-C01) exam is a great certification for those looking to validate their foundational knowledge of artificial intelligence (AI) and machine learning (ML) within the AWS ecosystem thanks amazon-dumps.com. It focuses on core AI concepts, AWS services like SageMaker, Rekognition, and Lex, as well as key best practices for implementing AI solutions in real-world scenarios. The exam is well-suited for professionals who want to build a career in AI and ML, providing a solid foundation for more advanced certifications. With the growing adoption of AI, this certification is a valuable credential for anyone looking to enhance their expertise and advance in the AI field.

upvoted 8 times

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Kendal_Ki

Highly Voted 3 weeks, 5 days ago

Selected Answer: B

The most relevant options for transparency and explainability are B and D. But B is the closest one as I studied in the pro version of guide from examtopicspro.com bcoz By focusing on PDPs and convergence tables, the AI practitioner can provide a clear and understandable explanation of the model's behavior without delving into technical details.

upvoted 7 times

Bella_hd

2 weeks, 5 days ago

Fully Satisfied

upvoted 3 times

Sarah_Sh

2 weeks, 4 days ago

yeah truly pro ones

upvoted 4 times

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jove

Most Recent 4 weeks, 1 day ago

Selected Answer: B

B. Partial Dependence Plots (PDPs) Explanation: Partial Dependence Plots (PDPs) are useful tools for understanding the relationship between specific features and the model's predictions, making it easier to see how changes in input variables affect the forecast. PDPs are particularly helpful for stakeholders because they visually show the impact of individual features on predictions without requiring a deep understanding of the model's inner workings.

upvoted 3 times

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sacha12

4 weeks, 1 day ago

I think B is correct

upvoted 1 times

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p2pcerts

1 month ago

B. Partial dependence plots (PDPs)

upvoted 5 times

Seraphina1

4 days, 8 hours ago

Nice take on PDPs! p2pcerts looks like a great resource too!

upvoted 1 times

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