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Hands-On Edge AI on UNO Q: How to Train and Deploy Custom ML Models

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Train a specialised model in Edge Impulse and deploy it into an Arduino App Lab application.

In this hands-on virtual workshop you will see how to train a specialised local machine learning model in Edge Impulse and integrate it into a pre-built application running on the Arduino UNO Q.

The workshop is designed as a practical follow-on to the webinar. Where the webinar shows how to build an application around a pre-trained model using agentic AI, this session focuses on the model workflow itself: collecting data, configuring a model, training it in Edge Impulse, exporting it, deploying it into Arduino App Lab and testing it on hardware.

You will be guided through the key development stages, from setup through to deployment and troubleshooting. The session will show how Edge Impulse and Arduino App Lab can work together to simplify the path from model training to embedded application development.

What you’ll learn

  • How to set up Edge Impulse for a custom Edge AI model workflow
  • How to prepare the Arduino UNO Q for model deployment
  • How to collect data and configure training parameters in Edge Impulse
  • How to train a specialised model for a local embedded use case
  • How to export an Edge Impulse model and bring it into Arduino App Lab
  • How to insert the model into a pre-built application
  • How to test the deployed model on the Arduino UNO Q
  • How to troubleshoot common setup, deployment and runtime issues

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