Create and train a PyTorch model for digit classification using the MNIST dataset

About this Learning Path

Who is this for?

This is an advanced topic for software developers interested in learning how to use PyTorch to create and train a feedforward neural network for digit classification, and also software developers interested in learning how to use and apply optimizations to the trained model in an Android application.

What will you learn?

Upon completion of this learning path, you will be able to:

• Prepare a PyTorch development environment.
• Download and prepare the MNIST dataset.
• Create and train a neural network architecture using PyTorch.
• Create an Android app and load the pre-trained model.
• Prepare an input dataset.
• Measure the inference time.
• Optimize a neural network architecture using quantization and fusing.
• Deploy an optimized model in an Android application.

Prerequisites

Before starting, you will need the following:

• A machine that can run Python3, Visual Studio Code, and Android Studio.
• For the OS, you can use Windows, Linux, or macOS.