About
The ML Fundamentals skill provides a comprehensive framework for building production-ready machine learning workflows within Claude. It streamlines the transition from raw data to trained models by providing standardized patterns for missing value imputation, feature scaling, and categorical encoding. By prioritizing scikit-learn pipelines and rigorous cross-validation strategies, the skill ensures developers avoid common pitfalls like data leakage while maintaining reproducible, high-quality code for both classification and regression tasks.