This web application is designed to predict the likelihood of a person having diabetes based on various health metrics. It utilizes a machine learning model trained on a dataset containing information about patients' health attributes.
To run the web application locally on your machine, follow these steps:
Navigate to the Project Directory:
bash Copy code cd diabetes_prediction_webapp Install Dependencies:
bash Copy code pip install -r requirements.txt Run the Application:
bash Copy code python -m streamlit run diabetes_prediction_webapp.py Access the Web App: Once the application is running, open your web browser and go to http://localhost:8501 to access the web interface.
Usage Upon accessing the web application, you'll be presented with a form where you can input various health metrics such as glucose level, blood pressure, BMI, etc. Fill in the required information and click on the "Predict" button. The model will then analyze the input data and predict the likelihood of diabetes for the provided health metrics. The prediction result will be displayed on the screen. Model Details The prediction model used in this web application is based on [provide details of your model here if needed].
Dataset The machine learning model was trained on a dataset containing [describe the dataset briefly, including its source if applicable].
About This web application was created by [Your Name] as a project for [provide context if applicable].
If you have any questions or suggestions, feel free to reach out to [your contact information].
vbnet Copy code
Feel free to customize it according to your project's specifics!