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Why the handling of imbalanced data sources is a critical skill for professional data scientists. Learn to apply resampling, cost-sensitive learning, and evaluation metrics correctly in this technical guide. Avoid common reporting errors and ensure your results are accurate, robust, and scientifically defensible across all your projects.