Scale even with a low budget

Have you ever wanted to build a machine learning application with a heavy model on the backend, a React user-friendly interface on the frontend, and a serverless cloud architecture all around so that your product is scalable to tens, hundreds, or even thousands of users?

Well, this is not as difficult as it sounds, and in this article, I will show how to build an application like this. To make this tutorial a bit fun, I’ll walk through the process of building Cartoonify.

Cartoonify is a toy application I made from scratch to turn pictures into cartoons. I know this may seem a bit funny, but believe me, there is serious work behind this app that you can leverage elsewhere. I’ll let you read this article to believe me or check the code on my  GitHub_._

Here’s what motivated me in starting this project

  • Give generative adversarial networks (GANs) a try. I’ve been fascinated by these models lately. Trying the CartoonGAN model to turn your face into a cartoon seemed like real fun.
  • Learn about deploying an application on a serverless architecture using different services of AWS (Lambda, API Gateway, S3, etc.).
  • Practice my React skills. I was used to Plotly, Dash, and Streamlit, and I wanted, for once, to build something custom and less mainstream.
  • Use Netlify to deploy this React app. I saw demos of how easy this process was, and I wanted to try it to convince myself.

#serverless #aws #programming #deep-learning

How to Build and Deploy A Serverless Machine Learning App on AWS
1.45 GEEK