Overview This repository contains code for analyzing heart disease risk factors and building a predictive model using Python libraries such as Pandas, NumPy, Seaborn, Plotly, and Scikit-learn. The primary objectives are to explore the dataset, identify risk factors, and develop a predictive model for heart disease.
The dataset used: Heart_2020_cleaned.csv
data_analysis.ipynb: Jupyter Notebook containing the code for exploratory data analysis and model building.
Pandas NumPy Seaborn Matplotlib Plotly Scikit-learn Datasist Imbalanced-learn (for SMOTE) Steps and Analysis