This repository contains a Streamlit web application for predicting insurance claim amounts based on user input. The predictive model is trained using machine learning techniques.

1. Clone the Repository:

   git clone https://github.com/MuhammadSheraza002/insurance-claim-prediction.git
   cd insurance-claim-prediction

2. Install Dependencies:

   pip install -r requirements.txt

3. Run the App:

   streamlit run app.py

4. Open in Browser: Visit http://localhost:8501 in your web browser.

The web application allows users to input various parameters such as age, gender, BMI, blood pressure, diabetic status, number of children, smoker status, and region. After providing the input, the user can click the "Predict" button to receive an estimated insurance claim amount.

• app.py: The main application file containing the Streamlit app.
• insurance.pkl: Pickle file containing the trained machine learning model.
• requirements.txt: File listing the Python dependencies for the project.

The predictive model is trained on an insurance dataset, and the trained model is saved using pickle. For details on the model training, refer to the original project code.

If you'd like to contribute or report issues, please open an issue or create a pull request.