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Streamline the data preparation phase of machine learning projects by automatically dividing datasets into optimized subsets. This skill interprets user-defined proportions to generate and execute Python code that splits data into training, validation, and testing sets while maintaining data integrity. By implementing best practices like stratification for imbalanced classes and randomization to prevent bias, it ensures that your data is properly partitioned for robust model development and evaluation.
