This project builds a simple ML model ins sci-kit learn and deploys it on a flask app.
File model.py builds ML model and saves it as pickle file.
server.py builds a flask server which loads the saved model and listens to incoming request. A request comes as JSON payload and it is forwarded to model which makes predictions. Upon making predictions, it is sent back to client as a JSON response.
Using python's request module this file makes http request to flask server.