Hands-on Tutorial
Part 2 — End to End Machine Learning Model Deployment Using Flask
How to build a user interface for loan approval prediction app and set up the backend using flask
After developing a robust machine learning model using xgboost in the previous part, in this article, we will focus our attention on the development of the user interface and the backend logic. Thus, we will discuss a lot about the HTML, CSS, and Python logic using flask. All of the necessary files are able to be downloaded so you can demonstrate this tutorial on your own computer.
Good luck! Let’s scroll down.
Our motivation
As data scientists, we’ve developed a machine-learning model for loan approval prediction. Now, we must create a friendly user interface for the loan approval prediction app which will be used by the user to automatically make an initial decision about the customer loan request. Fortunately, there are many websites that provide the HTML template just for free. As a developer, we don’t even need to design both HTML and CSS from scratch. For this tutorial, we use the template that comes from colorlib.
For the tutorial, you can first download the following repo. It also includes the…
