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PROFESSIONAL-MACHINE-LEARNING-ENGINEER · Question #320

PROFESSIONAL-MACHINE-LEARNING-ENGINEER Question #320: Real Exam Question with Answer & Explanation

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Submitted by carter_n· Apr 18, 2026Data processing and feature engineering

Question

You are developing a natural language processing model that analyzes customer feedback to identify positive, negative, and neutral experiences. During the testing phase, you notice that the model demonstrates a significant bias against certain demographic groups, leading to skewed analysis results. You want to address this issue following Google's responsible AI practices. What should you do?

Options

  • AUse Vertex AI's model evaluation to assess bias in the model's predictions, and use post-
  • BImplement a more complex model architecture that can capture nuanced patterns in language to
  • CAudit the training dataset to identify underrepresented groups and augment the dataset with
  • DUse Vertex Explainable AI to generate explanations and systematically adjust the predictions to

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Topics

#Bias mitigation#Responsible AI#Training data#Data augmentation
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