Build, optimize, and deploy ML models with ONNX on Arm64 and mobile devices

About this Learning Path

Who is this for?

This is an advanced topic for developers who want to build, optimize, and deploy machine learning models using ONNX on Arm64-based platforms such as Raspberry Pi, Arm-based laptops, cloud instances, or Android smartphones.

What will you learn?

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

• Explain what ONNX is and how it enables model portability across ML frameworks
• Build and export a neural network model in Python to ONNX format
• Run inference using ONNX Runtime on Arm64 platforms
• Apply model optimization techniques to improve performance
• Deploy an optimized ONNX model in an Android application

Prerequisites

Before starting, you will need the following:

• A development machine with Python 3.10 or 3.11 installed (Prebuilt ONNX Runtime packages for Arm platforms don’t yet support Python 3.12)
• Basic familiarity with PyTorch or TensorFlow
• An Arm64 device such as a Raspberry Pi or Android smartphone
• Android Studio (required only for the final deployment section)