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heart-disease-prediction
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# ❤️ Heart Disease Prediction A Machine Learning project that predicts the likelihood of heart disease using clinical data and Python. This repository contains the data analysis, model training, and evaluation steps used to build a predictive model. --- ## 📌 Overview This project uses a heart disease dataset to train a machine learning model that can classify whether a patient is likely to have heart disease based on input features such as age, cholesterol levels, blood pressure, and more. The goal is to demonstrate a complete ML workflow — from data preprocessing and exploration, to model training and evaluation. --- ## 🚀 Features ✔ Data cleaning and preprocessing ✔ Exploratory Data Analysis (EDA) ✔ Machine Learning model training and evaluation ✔ Visualization of insights ✔ Predictive model accuracy comparison --- ## 🧠 Tech Stack | Tool / Technology | Purpose | |-------------------|---------| | Python | Programming language | | Jupyter Notebook | Development environment | | NumPy & Pandas | Data manipulation | | Scikit-learn | Machine Learning | | Matplotlib & Seaborn | Visualization | --- ## 📁 Project Structure --- ## 📊 Dataset The dataset contains clinical and diagnostic features of patients relevant to heart disease, such as: - Age - Sex - Chest pain type - Resting blood pressure - Cholesterol - Maximum heart rate - And more… > ⚠️ Make sure you include your dataset file or download reference in your repo if not already present. --- ## 🛠️ Installation 1. **Clone the repository** ```bash git clone https://github.com/AGNELRENO/heart-disease-prediction.git
