Dim Sum Classifier – from Data to App part 2

Thu, 15 Aug 2019 12:00:52 +0000

Picture Credits here

In the previous post, we see how we can acquire data, process, clean and train an Image Classifier to identify some yummy dim sums.

In this post, we shall look at completing the loop by developing the web app using starlette (a framework similar to that of flask but supports asynchronous IO), setting up and automating deployment of our web app with Github, Docker contanier and Render.

The very helpful fast.ai course team and community has given us a quick start with the following resources:

Docker on Yoke Keong

Dim Sum Classifier – from Data to App part 2