Instruction: Explain how the quality of data affects the training and performance of machine learning models.
Context: This question assesses the candidate's understanding of the foundational role of data in machine learning and the implications of data quality on model outcomes.
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The way I'd explain it in an interview is this: Data quality sets the ceiling on model quality. If the labels are wrong, the features are stale, the joins are broken, or the training data does not represent the production population, the model will learn the wrong...