# Diabetes Prediction Web App
Welcome to the Diabetes Prediction Web App project. In this project, we have deployed a public machine learning web app using Streamlit. The main objective of this web app is to provide users with an intuitive interface to interact with a Support Vector Machine (SVM) classifier model. The model's purpose is to predict whether a person, with specific features, is likely to have Diabetes or not.
Web App Link: Diabetes Prediction Web App
The web app allows users to input various health-related features, and the SVM model processes the data to make a Diabetes prediction.
The machine learning model used in this project is an SVM classifier. It is trained on a labeled dataset to predict the likelihood of a person having Diabetes.
The model is saved as a binary file named model.sav.
The project is organized as follows:
mdps_public.py: This Python script contains the Streamlit code that powers the web app.diabetes_model.sav: The pre-trained SVM classifier model saved as a binary file.requirements.txt: This file lists all the necessary libraries and their versions for easy setup.web_app_screenshot.png: A screenshot of the web app for reference.
To run this project on your local machine, follow these steps:
- Python 3.x
- Install the required libraries from
requirements.txt:
pip install -r requirements.txt