Diabetes Prediction Project

Overview

This machine learning project aims to predict the risk of diabetes in individuals based on relevant health data. The prediction model utilizes a dataset of medical records and employs various machine learning techniques to provide early risk assessments for diabetes. By leveraging this predictive tool, healthcare providers can identify high-risk patients and initiate preventive measures, ultimately improving healthcare outcomes.

Table of Contents

• Dataset
• Installation
• Usage
• Contributing
• License

Dataset

The dataset used in this project can be found in the data directory. It includes both raw and processed data files. The preprocessing steps are documented in the Jupyter notebooks in the notebooks folder.

Installation

To set up the project environment, you can use the following steps:

1. Clone the repository:

   git clone https://github.com/yourusername/diabetes-prediction.git
   cd diabetes-prediction
   

2. Install the required dependencies using pip:

pip install -r requirements.txt

Usage

To run the project, follow these steps:

1. Navigate to the src directory:

   cd src

2. Run the main script:

   python main.py

3. Follow the prompts to input the necessary data or customize the prediction process.

Contributing

Contributions are welcome! If you'd like to contribute to this project, please follow these steps:

1. Fork the repository.
2. Create a new branch for your feature or bug fix.
3. Make your changes and commit them with descriptive messages.
4. Push your changes to your forked repository.
5. Create a pull request to merge your changes into the main branch of this repository.

License

This project is licensed under the MIT License.

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Feel free to customize this README.md file with more specific information about your project, including model details, results, and any additional resources or references. Good luck with your diabetes prediction project!