
Explored the UCI Cleveland heart-disease dataset in a Python notebook, comparing Logistic Regression, K-Nearest Neighbours and Random Forest against a binary target.
The work covers exploratory plots, a train/test split, randomised and grid searches, and five-fold cross-validation. I used ROC curves, confusion matrices, precision, recall and F1 to examine predictions, then inspected the logistic-regression coefficients.






