Deploy Machine Learning Model using Flask to Heroku — Part 1

You have just learned how to create machine learning models. You model is working as you would like it to. But then you have one dilemma, how to take your model from your notebook and package it as a product that people can use with ease.

This tutorial aims to give an introduction to Machine Learning beginners on how to create and deploy machine learning models.

1. The first part will be a walkthrough of the machine learning model. This tutorial however assumes that you have basic knowledge of machine learning models, and therefore the notebook has not covered in depth aspects of data pre-processing and model implementation. The notebook and the rest of the flask, html code can be found on GitHub using this link https://github.com/Jnjerry/diabetespredictor. Link to the first part  which is was about data pre-processing and creation of a logistic regression model using JupyterNotebook
2. The second part will be a guide on how to embed your machine learning model into a flask application for the model to be used as a web application.
3. The third part will be a guide on how to deploy your machine learning to Heroku via GitHub. You can find the final output here https://joan-diabetes-predictor.herokuapp.com/.