Edge AI on Arm: PyTorch and ExecuTorch rock-paper-scissors

About this Learning Path

Who is this for?

This is an introductory topic for machine learning developers who want to deploy TinyML models on Arm-based edge devices using PyTorch and ExecuTorch.

What will you learn?

Upon completion of this Learning Path, you will be able to:

• Train a small Convolutional Neural Network (CNN) for image classification using PyTorch
• Use synthetic data generation for training a model when real data is limited
• Convert and optimize a PyTorch model to an ExecuTorch program (`.pte`) for Arm-based devices
• Run the trained model locally as an interactive mini-game to demonstrate inference

Prerequisites

Before starting, you will need the following:

• Basic understanding of machine learning concepts
• Familiarity with Python and the PyTorch library
• Completion of the Learning Path Introduction to TinyML on Arm using PyTorch and ExecuTorch
• An x86 Linux host machine or VM running Ubuntu 22.04 or later