This repository contains a machine learning project aimed at predicting the likelihood of heart disease using logistic regression. The goal is to develop a robust predictive model based on patient health data to assist in early detection and risk assessment of heart-related ailments.
*Data Preprocessing: Comprehensive preprocessing techniques to clean and handle missing data in the dataset.
*Logistic Regression Model: Implementation of logistic regression for binary classification to predict the presence or absence of heart disease.
*Performance Evaluation: Evaluation metrics like accuracy, precision, recall, and F1-score to assess the model's performance.