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Exam Professional Machine Learning Engineer All Questions

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Exam Professional Machine Learning Engineer topic 1 question 75 discussion

Actual exam question from Google's Professional Machine Learning Engineer
Question #: 75
Topic #: 1
[All Professional Machine Learning Engineer Questions]

You work at a subscription-based company. You have trained an ensemble of trees and neural networks to predict customer churn, which is the likelihood that customers will not renew their yearly subscription. The average prediction is a 15% churn rate, but for a particular customer the model predicts that they are 70% likely to churn. The customer has a product usage history of 30%, is located in New York City, and became a customer in 1997. You need to explain the difference between the actual prediction, a 70% churn rate, and the average prediction. You want to use Vertex Explainable AI. What should you do?

  • A. Train local surrogate models to explain individual predictions.
  • B. Configure sampled Shapley explanations on Vertex Explainable AI.
  • C. Configure integrated gradients explanations on Vertex Explainable AI.
  • D. Measure the effect of each feature as the weight of the feature multiplied by the feature value.
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Suggested Answer: B 🗳️

Comments

Chosen Answer:
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PhilipKoku
4 months, 3 weeks ago
Selected Answer: B
B) Shapley
upvoted 2 times
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pmle_nintendo
8 months ago
Selected Answer: B
Sampled Shapley explanations offer a more sophisticated and model-agnostic method for understanding feature importance and contributions to predictions.
upvoted 3 times
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adavid213
11 months, 4 weeks ago
Selected Answer: B
I agree, it seems like B
upvoted 1 times
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NickHapton
1 year, 4 months ago
B refer: https://cloud.google.com/vertex-ai/docs/explainable-ai/overview#compare-methods
upvoted 2 times
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M25
1 year, 5 months ago
Selected Answer: B
Went with B
upvoted 2 times
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CloudKida
1 year, 5 months ago
Selected Answer: B
Assigns credit for the outcome to each feature, and considers different permutations of the features. This method provides a sampling approximation of exact Shapley values. shampled shapely recommended Model Type: Non-differentiable models, such as ensembles of trees and neural networks. https://cloud.google.com/ai-platform/prediction/docs/ai-explanations/overview
upvoted 2 times
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enghabeth
1 year, 8 months ago
Selected Answer: B
Sampled Shapley works well for these models, which are meta-ensembles of trees and neural networks. https://cloud.google.com/vertex-ai/docs/explainable-ai/overview#sampled-shapley
upvoted 2 times
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John_Pongthorn
1 year, 9 months ago
Selected Answer: B
B is optimal for tabular data Tree or DNN C integrated gradients explanations on Vertex Explainable AI. It is used for image.
upvoted 2 times
John_Pongthorn
1 year, 9 months ago
https://cloud.google.com/vertex-ai/docs/explainable-ai/overview#compare-methods
upvoted 3 times
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ares81
1 year, 9 months ago
Selected Answer: B
It should be B.
upvoted 1 times
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emma_aic
1 year, 10 months ago
Selected Answer: B
https://cloud.google.com/vertex-ai/docs/explainable-ai/overview#sampled-shapley
upvoted 2 times
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egdiaa
1 year, 10 months ago
B - For sure as per GCP Docs here: https://cloud.google.com/vertex-ai/docs/explainable-ai/overview
upvoted 1 times
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hiromi
1 year, 10 months ago
Selected Answer: B
B - https://christophm.github.io/interpretable-ml-book/shapley.html - https://cloud.google.com/vertex-ai/docs/explainable-ai/overview
upvoted 2 times
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JeanEl
1 year, 10 months ago
Selected Answer: B
Agree with B : individual instance prediction + ensemble of trees and neural networks (recommended model types for Sampled Shapley : "Non-differentiable models, such as ensembles of trees and neural networks " ). Check out the link below : https://cloud.google.com/vertex-ai/docs/explainable-ai/overview
upvoted 3 times
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YangG
1 year, 10 months ago
Selected Answer: C
it is about a individual instance prediction. I think use integrated gradient method
upvoted 2 times
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ares81
1 year, 10 months ago
It seems D.
upvoted 1 times
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