ML-Model-Heroku-Deployment

This is My First project to elaborate how Machine Learn Models are deployed on production using Flask API on the Local Computer as Well as Heroku

Prerequisites

You must have Scikit Learn, Pandas (for Machine Leraning Model) and Flask (for API) installed.

Project Structure

This project has four major parts :

1. untitled3.ipynb - This contains code fot our Machine Learning model to predict employee salaries absed on training data in 'hiring.csv' file.
2. app.py - This contains Flask APIs that receives employee details through GUI or API calls, computes the precited value based on our model and returns it.
3. templates(index.html)/Static(css) - This folder contains the HTML template to allow user to enter employee detail and displays the predicted employee salary and some simple styling using Style.css.

Running the project

1.Create the machine learning model by running below File in google collab -

 untitled3.ipynb

This would create a serialized version of our model into a file model.pkl

2. Run app.py using below command to start Flask API

python app.py

By default, flask will run on port 5000

3. Navigate to localhost URL http://127.0.0.1:5000/

You Can Also Deploy the Model on Heroku

https://salary-p.herokuapp.com/predict

You should be able to view the homepage as below :

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

If everything goes well, you should be able to see the predcited salary vaule on the HTML page!