🫀 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.
python machine-learning numpy machine-learning-algorithms jupyter-notebook pandas artificial-intelligence dataset supervised-learning classification learning-material logistic-regression-algorithm heart-disease accuracy-score train-test-split heart-disease-prediction sckit-learn
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Updated
Jul 25, 2025 - Jupyter Notebook