AIF-C01 Question 53
Select 3An e-commerce company uses a machine learning (ML) model to recommend products to its users. The model’s performance has been degrading over time due to changes in customer behavior. The company wants to ensure that the model performs optimally in production by implementing an MLOps strategy. Which of the following steps should be included in their MLOps process to address this issue?
- A
Set up automated monitoring to track model performance metrics such as accuracy and precision.
- B
Implement a manual process to retrain the model every six months, regardless of performance metrics.
- C
Establish a pipeline to automatically retrain and deploy the model when performance drops below a threshold.
- D
Archive the current dataset and replace it entirely with new data without analyzing its impact on the model.
- E
Continuously collect and label new data that reflects the latest customer behavior for retraining.
Show answer and explanation
Correct answers: A, C, E
Explanation
To address performance degradation in production, an MLOps strategy should include automated monitoring to detect issues early, pipelines to automate retraining and deployment when performance drops, and methods to continuously collect and label new data that reflects changes in user behavior. These steps create a scalable and repeatable process that ensures production readiness and minimizes technical debt.
- A. Correct.
Setting up automated monitoring is essential to track the model's performance in real time and identify when it starts to degrade.
- B. Incorrect.
A manual process for retraining every six months is not efficient or adaptive to changes in customer behavior, as it does not account for real-time performance metrics.
- C. Correct.
Establishing an automated retraining and deployment pipeline ensures that the model is updated promptly when performance falls below acceptable levels.
- D. Incorrect.
Archiving and replacing the dataset without analysis can lead to a loss of valuable historical data and may negatively impact the model's performance.
- E. Correct.
Collecting and labeling new data that reflects current trends ensures that the model is trained on relevant and up-to-date information, improving its accuracy.