Instruction for running

ML-Model-Flask-Deployment

This is the code for machine learn models using flask

Prerequisites

Scikit Learn, Pandas (for Machine Leraning Model) and Flask

Project Structure

This project has four major parts :

1. model.py - contains code fot our Machine Learning model
2. app.py - contains Flask APIs that receives details through GUI or API calls
3. request.py - uses requests module to call APIs and dispalys the returned value.
4. templates - This folder contains the HTML template

Running the project

1. Create the machine learning model

python model.py

This creates serialized version of our model into model.pkl

2. Run app.py using below command

python app.py

Flask should run on port 5000.

3. Navigate to http://localhost:5000

You should be able to view the homepage

Enter valid numerical values in all 3 input boxes and hit Predict.

4. Can also send direct POST requests to FLask API using Python's inbuilt request module

Below command to send the request with some pre-popuated values -

python request.py