❤ Heart Disease Prediction from Medical Data This project uses machine learning models to predict the likelihood of heart disease based on patient medical data. It demonstrates a full machine learning pipeline including data preprocessing, visualization, model training, and evaluation.
📊 Features Data loading and preprocessing from CSV
Exploratory Data Analysis (EDA)
Feature selection and encoding
Model training using:
Logistic Regression
Decision Tree
Random Forest
Support Vector Machine (SVM)
Model performance evaluation (accuracy, confusion matrix)
Prediction on new data
🧰 Tech Stack Python 3.x
Libraries:
pandas
numpy
matplotlib
seaborn
scikit-learn
warnings