PROFESSIONAL-MACHINE-LEARNING-ENGINEER · Question #320
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…
The correct answer is C. Audit the training dataset to identify underrepresented groups and augment the dataset with. Auditing and augmenting the training dataset to improve representation of underrepresented groups directly addresses the root cause of model bias. This aligns with Google's responsible AI practices, which emphasize fairness by improving data quality and representation before…
Question
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
How the community answered
(68 responses)- A13% (9)
- B3% (2)
- C76% (52)
- D7% (5)
Explanation
Auditing and augmenting the training dataset to improve representation of underrepresented groups directly addresses the root cause of model bias. This aligns with Google's responsible AI practices, which emphasize fairness by improving data quality and representation before relying on post-processing or model adjustments.
Topics
Community Discussion
No community discussion yet for this question.