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Answer: Train the model by selecting and preparing relevant training data, using techniques such as data augmentation and cross-validation.
Training the model by selecting and preparing relevant training data, using techniques such as data augmentation and cross-validation, ensures that the model learns effectively and handles various retail-related queries. This approach helps in improving the model's performance and accuracy.
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You need to train a language understanding model for a retail application. Describe the process you would follow to train the model, including how you would select and prepare the training data, and what techniques you would use to ensure the model learns effectively and handles various retail-related queries.
A
Train the model using random data without any preparation.
B
Train the model by selecting and preparing relevant training data, using techniques such as data augmentation and cross-validation.
C
Train the model without selecting any training data.
D
Train the model by only using generic training data.
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