icbaptista/heart-disease-prediction-with-ML

This project involved a comprehensive analysis of machine learning models, including LogisticRegression, KNearestNeighbors, NeuralNetworks, SupportVectorMachine, and RandomForest, to compare their effectiveness in predicting heart disease using the Cleveland heart disease dataset.

Jupyter Notebook