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For supervised learning, the "ground truth" labels must be flawless. 3. The Challenges of Data Quality in LLMs

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✅ Data engineers & ML engineers ✅ AI product managers ✅ Data governance leads ❌ Beginners without basic SQL/Python knowledge (some papers assume familiarity with data warehouses) For supervised learning, the "ground truth" labels must

Are there missing values that could skew model learning? For supervised learning

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Is the data up-to-date enough to represent current trends?