This article focuses on deploying machine learning models using mnist handwritten digit recognition as a base example implemented in tensorflow-2. In the end, we will be cooking up a small web app in React to test our model. If you are a machine learning enthusiast then you already know that mnist digit recognition is the hello world program of deep learning and by far you have already seen way too many articles about digit-recognition on medium and probably implemented that already which is exactly why I won’t be focusing too much on the problem itself and instead show you how you can deploy your models and consume them in production. To see the end result you can view the deployed-app here

Before jumping into deployments I will quickly give you a brief walkthrough of the model and show you how you can save your model and consume it in production later on. If you are tired of reading about handwritten-digit-recognition like me you can skip this portion and use the github-repo to get the model so you can follow the rest of the guide.

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