Topic 1 Question 247
You built a deep learning-based image classification model by using on-premises data. You want to use Vertex AI to deploy the model to production. Due to security concerns, you cannot move your data to the cloud. You are aware that the input data distribution might change over time. You need to detect model performance changes in production. What should you do?
Use Vertex Explainable AI for model explainability. Configure feature-based explanations.
Use Vertex Explainable AI for model explainability. Configure example-based explanations.
Create a Vertex AI Model Monitoring job. Enable training-serving skew detection for your model.
Create a Vertex AI Model Monitoring job. Enable feature attribution skew and drift detection for your model.
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- 正解だと思う選択肢: C
Option A and B: Vertex Explainable AI provides insights into model behavior but doesn't directly detect performance changes or concept drift. It's more suitable for understanding model decisions, not monitoring production performance. Option D: Feature attribution skew and drift detection requires feature attributions calculated during training, which might not be feasible without cloud access to the data.
👍 1pikachu0072024/01/13
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