A dockerized end to end ML Web app for web app for detection of diabetes among women with a high classification accuracy.
- Various plots to get detailed information about how different algortihms classify thereby affecting a diabetes diagnosis.
- Train and load your own custom models using various algorithms on the go.
- Look at raw data.
- Clean and Simple UX and UI :)
http://whispering-everglades-97562.herokuapp.com/
Note - The app takes time to load for first time.
- Git clone the repository
- Open CMD, navigate to cloned directory and run "pip install -r requirements.txt" This will install all the dependencies including Streamlit.
- In the project directory open a command prompt and enter "streamlit run app.py" This will start Streamlit locally.
I had already made this project for practice in a jupyter notebook but wanted to learn how to deploy ML models so that anyone can use them hence I decided to revisit the project and make a full fledged web app using streamlit. I then deployed a docker container of the webapp on Heroku