Hands-On Python Deep Learning for the Web

Summary

This chapter covered, in complete detail, how you can create a deep learning model and then facilitate its usage through an API via a web client or using cURL. The chapter began by discussing how deep learning web applications are structured, the various components of such applications, and how they interact with each other. Then, a short discussion and exploration of the MNIST handwritten digits dataset was presented. This led us on to the next section, where we built a deep learning model and stored it in files for future use. These files were then imported to the server API scripts and executed there whenever the API was called. Finally, the chapter presented a very basic client for the API and also instructed you on how to use ...