🫀 A machine learning project using logistic regression to predict heart disease risk from clinical data. Built with Python, scikit-learn, and Jupyter notebooks. Achieves 85%+ accuracy on 303-patient dataset with 13 medical features. Complete ML pipeline from data exploration to model evaluation.
☆16Jul 25, 2025Updated last year
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