Heart Disease Diagnostic Analysis ๐
Welcome to the Heart Disease Diagnostic Analysis project! This repository contains code and resources for analyzing heart disease diagnostic data.
This project aims to provide a comprehensive analysis of various factors contributing to heart disease diagnosis. Leveraging machine learning techniques, we strive to build models that accurately predict the presence or absence of heart disease based on patient data.
- Data Preprocessing: Clean and preprocess raw data to prepare it for analysis. ๐งน
- Exploratory Data Analysis (EDA): Gain insights into the dataset through visualizations and statistical summaries. ๐๐
- Model Development: Train and evaluate machine learning models for heart disease prediction. ๐ค๐
- Model Interpretation: Understand the factors influencing heart disease diagnosis through model interpretation techniques. ๐
- Deployment: Deploy trained models for real-world use cases. ๐
To get started with this project using Google Colab or Jupyter Notebook:
- Clone the repository:
git clone https://github.com/your_username/heart-disease-diagnostic-analysis.git
- Open the Jupyter notebooks in the
notebooks
directory using Google Colab or Jupyter Notebook. - Explore the notebooks for data analysis and model development.
- Experiment with different models and hyperparameters to improve predictive performance.
- Once satisfied with the model, deploy it for use in clinical settings. ๐ฅ
Feel free to reach out if you have any questions or suggestions. Happy analyzing! ๐ป๐ฌ