Diabetic Prediction

This GitHub repository contains code and resources for predicting diabetes using machine learning algorithms. The project utilizes the PIMA dataset and provides a streamlined way to run the prediction on Streamlit.

Instructions

To run this project on Streamlit, follow the steps below:

1. Clone the repository:

   git clone https://github.com/prakash02100/Diabetic_Prediction.git
   

2. Install the required dependencies:

   pip install -r requirements.txt
   

3. Run the Streamlit app:

   streamlit run app.py
   

4. The application will open in your default web browser, allowing you to interact with the prediction model.

Project Structure

• app.py: Contains the Streamlit application code for user interaction and displaying the prediction results.
• data: Directory containing the PIMA dataset or any additional data files required for the prediction.
• models: Directory to store trained machine learning models.
• utils.py: Utility functions and helper code used in the project.

Requirements

The following are the key requirements for running this project:

• Python 3.7+
• Streamlit
• Pandas
• NumPy
• Scikit-learn

You can install these dependencies by running the command mentioned in step 2 of the Instructions section.

Contributing

Contributions to this project are welcome! If you encounter any issues or have suggestions for improvements, please feel free to open an issue or submit a pull request.

License

This project is licensed under the MIT License.