https://github.com/shubham5027/diabetes-prediction-webapp-using-machine-learning

A Diabetes Prediction web app using machine learning is an application that utilizes a trained machine learning model to predict whether a person has diabetes based on input features such as glucose levels, blood pressure, BMI, age, etc.
https://github.com/shubham5027/diabetes-prediction-webapp-using-machine-learning

classification logi machine-learning numpy pandas plotly sklearn streamlit webapp

Last synced: about 2 months ago
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A Diabetes Prediction web app using machine learning is an application that utilizes a trained machine learning model to predict whether a person has diabetes based on input features such as glucose levels, blood pressure, BMI, age, etc.

• Host: GitHub
• URL: https://github.com/shubham5027/diabetes-prediction-webapp-using-machine-learning
• Owner: shubham5027
• Created: 2024-01-11T09:07:49.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2024-01-11T09:59:41.000Z (over 2 years ago)
• Last Synced: 2025-11-21T13:05:35.197Z (7 months ago)
• Topics: classification, logi, machine-learning, numpy, pandas, plotly, sklearn, streamlit, webapp
• Language: Jupyter Notebook
• Homepage: https://diabetes-prediction-webapp-using-machine-learning-fxgmyqg5kzjz.streamlit.app/
• Size: 156 KB
• Stars: 5
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Diabetes Prediction Web App

A Diabetes Prediction web app using machine learning is an application that utilizes a trained machine learning model to predict whether a person has diabetes based on input features such as glucose levels, blood pressure, BMI, age, etc

## Prerequisites

- Python

- Pip 

- Git (optional)

## Getting Started

1. **Clone the Repository:**

    ```bash

    git clone https://github.com/shubham5027/diabetes-prediction-webapp.git

    cd diabetes-prediction-webapp

    ```

2. **Install Dependencies:**

    ```bash

    pip install -r requirements.txt

    ```

3. **Run the App:**

    ```bash

    python -m streamlit run app.py

    ```

4. **Access the Web App:**

https://diabetes-prediction-webapp-using-machine-learning-fxgmyqg5kzjz.streamlit.app/

   

![Screenshot 2024-01-11 144256](https://github.com/shubham5027/Diabetes-Prediction-webapp-using-Machine-Learning/assets/132193443/1cf49525-f715-412f-b076-de9f0d4de095)

![Screenshot 2024-01-11 144308](https://github.com/shubham5027/Diabetes-Prediction-webapp-using-Machine-Learning/assets/132193443/63b77e4a-7c5b-4f4c-a7f0-3127947cdceb)

## Usage

- Use the sliders in the sidebar to input values for features like pregnancies, glucose, blood pressure, etc.

- Click the "Predict" button to see the model's prediction.

- The result will be displayed, indicating whether the person is predicted to have diabetes or not.

## Model Information

The machine learning model used in this app is a logistic regression model trained on the Diabetes dataset.

## Additional Notes

- The web app is built using Streamlit, a Python library for creating web applications with minimal effort.

- The trained machine learning model is saved in a file named `your_model.pkl`. Replace it with your actual trained model file.

## License

This project is licensed under the [MIT License](LICENSE).