Google Professional Machine Learning Engineer Question 410
Select 3Google Cloud PlatformYou are managing a machine learning model deployed on Google Cloud, which predicts customer churn for a subscription-based business. The model's performance has started to degrade due to changes in customer behavior. You decide to implement an automated model retraining pipeline using Vertex AI. Which of the following steps should you include to ensure successful automation of the retraining process?
- A
Monitor model performance metrics such as accuracy and F1 score to detect when retraining is required.
- B
Trigger the retraining pipeline based on a fixed schedule, without considering model performance.
- C
Set up a data pipeline to ensure the new training data is preprocessed and stored in BigQuery.
- D
Deploy the retrained model automatically without human validation to minimize latency.
- E
Integrate CI/CD practices to test and validate the retrained model before deployment.
Show answer and explanation
Correct answers: A, C, E
Explanation
Automating model retraining involves monitoring performance metrics, ensuring clean and preprocessed training data, and validating the retrained model before deployment. These steps help maintain model accuracy and reliability while minimizing risks associated with automation. Triggering retraining solely based on a fixed schedule or deploying without validation can lead to suboptimal outcomes.
- A. Correct.
Monitoring model performance metrics is essential to identify when the model's predictions are no longer reliable, indicating the need for retraining.
- B. Incorrect.
Triggering retraining solely based on a fixed schedule ignores the actual performance of the model and can lead to unnecessary retraining or delayed updates.
- C. Correct.
Setting up a data pipeline ensures that new training data is clean, preprocessed, and ready for use in retraining, which is a critical step in automation.
- D. Incorrect.
Automatically deploying a retrained model without validation can introduce risks, as the new model might perform worse than the previous one. Human validation or automated validation checks are crucial.
- E. Correct.
Integrating CI/CD practices ensures that the retrained model is rigorously tested and validated before deployment, reducing the chances of errors in production.