Exam AWS Certified Machine Learning - Specialty topic 1 question 36 discussion

Ans: D

The model performance degradation over time suggests concept drift—the relationship between input features and the target variable has changed. Since product recommendations depend on customer behavior, preferences, and product inventory, periodic retraining with updated data ensures the model adapts to these changes. Why Periodic Retraining? Customer preferences evolve: Buying patterns change over time due to seasons, trends, and external factors. New products get added, and old ones are discontinued: The model must learn about new items and stop recommending outdated ones. The dataset needs to reflect recent trends: Using new and historical data together ensures the model retains useful past knowledge while learning new patterns.

'retrained using the original training data plus new data'

I believe it should be B 1. The model performance has diminished gradually over the past few months, indicating the data distribution may have changed since initial deployment over a year ago. This is a classic sign of concept drift. 2. The model architecture and training procedure have remained unchanged since initial deployment. Updating the hyperparameters is a lighter approach than retraining the model from scratch, and can help prevent further performance deterioration if done periodically to adapt to changes in user preferences and product inventory.

Answer is D

D is the answer!

D is the answer. There has been a data drift resulting from new customer segment visiting the site. So, the model needs to be updated periodically with new data from the website.

DDDDD. D :D

Incremental training. D.

Periodically Re-Fit D

agree with D

D is correct