Python Deep Learning Projects

Building a common DL environment

Our main goal to achieve by the end of this chapter is to standardize the toolsets to work together and achieve consistently accurate results.

In the process of building applications using DL algorithms that can also scale for production, it's very important to have the right kind of setup, whether local or on the cloud, to make things work end to end. So, in this chapter, we will learn how to set up a DL environment that we will be using to run all the experiments and finally take the AI models into production.

First, we will discuss the major components required to code, build, and deploy the DL models, then various ways to do this, and finally, look at a few code snippets that will help to automate the ...