Exam Professional Machine Learning Engineer topic 1 question 333 discussion

Actual exam question from Google's Professional Machine Learning Engineer

Question #: 333
Topic #: 1

[All Professional Machine Learning Engineer Questions]

Your company's business stakeholders want to understand the factors driving customer churn to inform their business strategy. You need to build a customer churn prediction model that prioritizes simple interpretability of your model's results. You need to choose the ML framework and modeling technique that will explain which features led to the prediction. What should you do?

A. Build a TensorFlow deep neural network (DNN) model, and use SHAP values for feature importance analysis.
B. Build a PyTorch long short-term memory (LSTM) network, and use attention mechanisms for interpretability.
C. Build a logistic regression model in scikit-learn, and interpret the model's output coefficients to understand feature impact.
D. Build a linear regression model in scikit-learn, and interpret the model's standardized coefficients to understand feature impact.

Show Suggested Answer

Suggested Answer: C 🗳️

by Duke_CT at June 20, 2025, 3:52 a.m.

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Duke_CT

1 month, 4 weeks ago

Selected Answer: A

Definitely C in my opinion.

upvoted 1 times

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