Summary
This chapter was the longest one so far and quite intensive with the hands-on tasks. You've hopefully managed to follow along and learned how machine learning models built with TPOT can be deployed – both locally and to the cloud.
You are now capable of deploying any sort of machine learning model built with Python. Besides, you also know how to deploy basic Python web applications, provided that you have the necessary knowledge of frontend technologies, such as HTML, CSS, and JavaScript. We didn't dive into this area, as it's beyond the scope of this book.
In the following chapter, Chapter 9, Using the Deployed TPOT Model in Production, you'll learn how to build a basic application around this REST API. To be more precise, you'll learn how to make a simple and decent-looking web interface that predicts flower species based on the input data. But before that, you'll practice making a request to our API with Python.
As always, feel...
