Create digit recognition web app with Streamlit

In this 1-hour long project-based course, you will learn how to create a digit recognition web application using streamlit. This project is divided into two stages. In the first stage, you are going to write the training pipeline in which you will load MNIST Handwritten dataset. You will write the training and validation functions in order to train and validate the dataset. Lastly, in this stage you will do inference. In the second stage, you will use the best trained model from the training pipeline and you will use that in your web app. You will create the web user interface using streamlit python library. In this web app a user will draw a digit and given that drawn digit, the best trained model will output the probabilities.

• Project Overview
• In this 1-hour long project-based course, you will learn how to create a digit recognition web application using streamlit. This project is divided into two stages. In the first stage, you are going to write the training pipeline in which you will load MNIST Handwritten dataset. You will write the training and validation functions in order to train and validate the dataset. Lastly, in this stage you will do inference. In the second stage, you will use the best trained model from the training pipeline and you will use that in your web app. You will create the web user interface using streamlit python library. In this web app a user will draw a digit and given that drawn digit, the best trained model will output the probabilities.