Google Professional Data Engineer
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You are tasked with developing a model that generates clothing recommendations. Recognizing that a user's fashion preferences are likely to evolve over time, you have constructed a data pipeline that streams fresh data back to the model continuously as new information becomes available. Given this setup, what approach should you take to utilize this incoming data for training the model effectively?
Exam-Like
A
Continuously retrain the model on just the new data.
B
Continuously retrain the model on a combination of existing data and the new data.
C
Train on the existing data while using the new data as your test set.
D
Train on the new data while using the existing data as your test set.
Explanation:
The correct answer is B. Continuously retraining the model on a combination of existing data and the new data ensures that the model retains knowledge of historical preferences while also adapting to new trends. This approach prevents the model from becoming outdated or overfitting to the most recent data alone, which would reduce its generalization performance.
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