Diabetes-Prediction-ML-Web-App

Diabetes Prediction ML Web App. Includes machine learning models such as Logistic Regression, Random Forest, Gradient Boosting, and Support Vector Machine (SVM). For Web App - HTML, CSS and Django framework.

Screenshots

Dataset Details

• Dataset: Utilized a dataset containing 769 records and 9 columns, with 8 independent variables and 1 dependent variable (Outcome).

Machine Learning Models

• Logistic Regression
• Random Forest
• Gradient Boosting
• Support Vector Machine (SVM)

Accuracy Achievement

• Achieved an overall accuracy of approximately 75% across three models.
• SVM led the pack with an accuracy of 77%.

Platform

• Jupyter Notebook, PyCharm

Getting Started

To set up the project locally, follow these steps:

1. Clone this repository.
2. Open PyCharm and import the project.
3. Navigate to the WebApp directory and install the necessary dependencies.
4. Run the Django server to start the web application.

To run the Web App using the command prompt or terminal:

1. Open your command prompt or terminal.
2. Navigate to the directory where your Django project is located using the cd command.
3. Once you're in the project directory, run the following command to start the
   Django development server: python manage.py runserver
4. Open a web browser and go to http://127.0.0.1:8000/ to access the web application.

Demo Video

Check out the demo video showcasing the functionality of the web application

Contributing

Contributions are welcome! Feel free to open issues or pull requests for any improvements or bug fixes.