This project is a heart disease prediction model developed using Jupyter Notebook. The model follows a comprehensive data analytics process and is trained on over 300 models to achieve high accuracy in predicting heart disease.
- Predictive Capability: Accurately predicts the likelihood of heart disease in patients.
- High Accuracy: Achieves over 90% accuracy in predictions.
- Model Training: Utilizes a robust training process involving over 300 models.
To run this model, you will need the following libraries:
- Python 3.x
- Jupyter Notebook
- Pandas
- NumPy
- Scikit-learn
- Matplotlib
- Seaborn (optional, for enhanced visualization)
You can install the necessary libraries using pip
:
pip install pandas numpy scikit-learn matplotlib seaborn