Creating Your First Deep Learning Web Application

After developing an understanding of neural networks and their setup for use in real-world projects, the natural next step is to develop a web-based deep learning application. This chapter is dedicated to creating a complete web application—albeit a very simplistic one—that, in a very simple way, demonstrates how the integration of deep learning in applications is done.

This chapter will introduce several terms that will be used throughout this book, and so it is a recommended read even for those of you who already have a basic understanding of deep learning web applications so that you are able to understand the terms used in future chapters. We will begin by structuring a deep learning web application and learning how to understand datasets. We will then implement a simple neural network using Python and create a Flask API to work with server-side Python.

In this chapter, the following topics will be covered:

• Structuring a deep learning web application
• Understanding datasets
• Implementing a simple neural network using Python
• Creating a Flask API that works with server-side Python
• Using cURL and the web client with Flask
• Improving the deep learning backend