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AI-102 Practice Question: Implement natural language processing solutions
A company uses Azure AI Language Service for custom text classification. The model is trained to classify support tickets into categories. After deployment, the model performs well on the test set but poorly on new incoming tickets. Which action should be taken to improve generalization?
⚠ Common exam trap
Candidates often mistakenly tune hyperparameters (epochs, confidence threshold) or switch to a prebuilt model, but the real issue is distribution shift between test data and production data. Adding representative labeled data from production is the correct solution.
Correct answer & explanation
Adding more labeled data from actual production tickets helps the model learn the true distribution of real-world inputs, reducing overfitting to the test set. The model's poor performance on new tickets indicates it memorized patterns specific to the training data rather than generalizing. Incorporating production data directly addresses the distribution shift between the test set and live traffic.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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