Chapter 11: Deploying Models with Flask Applications
Over the course of this book, we explored the development of numerous robust machine learning models in areas such as breast cancer detection, scientific topic modeling, protein classification, and molecular property prediction. In each of these tutorials, we prepared and validated our models to allow them to have the best predictive power possible. We will now pivot from the development of new models to the deployment of trained models to our end users.
Within this chapter, we will explore one of the most popular frameworks for the preparation of web applications: Flask. We will use Flask to prepare a web application to serve our models to end users, and we will also prepare an Application Programming Interface (API) to serve our predictions to other web applications.
Over the course of this chapter, we will cover the following topics:
- Understanding API frameworks
- Working with Flask and Visual Studio Code ...
