Machine Learning at the Edge on Arm: A Practical Introduction

Machine Learning at the Edge on Arm: A Practical Introduction

The age of machine learning has arrived! Arm technology is powering a new generation of connected devices with sophisticated sensors that can collect a vast range of environmental, spatial and audio/visual data. Typically this data is processed in the cloud using advanced machine learning tools that are enabling new applications reshaping the way we work, travel, live and play.

To improve efficiency and performance, developers are now looking to analyse this data directly on the source device – usually a microcontroller (we call this ‘the Edge[’). But with this approach comes the challenge of implementing machine learning on devices that have constrained computing resources.

By enrolling in Machine Learning at th e Edge on Arm: A Practical Introduction you’ll learn how to train machine learning models and implement them on industry relevant Arm-based microcontrollers.

We’ll start your learning journey by taking you through the basics of AI, ML and ML at the Edge, and illustrate why businesses now need this technology to be available on connected devices. We’ll then introduce you to the concept of datasets and how to train ML algorithms using tools like Anaconda and Python. We'll then go on to explore advanced topics such as Artificial Neural Networks and Computer Vision.