Implement a neural network model for performing real-time image classification on a secured, internet-connected microcontroller-based device (Azure Sphere). Describe the components and steps for implementing a pre-trained image classification model on Azure Sphere.
Implement image classification on a microcontroller device using a pre-trained neural network model. Describe how the components and services of an Azure Sphere work to deploy a pre-trained image classification model. "Produced in partnership with the University of Oxford – Ajit Jaokar Artificial Intelligence:Cloud and Edge Implementations course."
- Basic knowledge of Azure Sphere
- USB cable to connect Azure Sphere to the computer
- USB-to-serial adapter
- Mini cable to connect serial adapter to the computer
- Jumper wires to connect serial adapter to Azure Sphere
- Basic knowledge of using Visual Studio Code
- Visual Studio Code installed in your computer
- Git installed in your computer
- Ability to use Git/Github
- Introduction - 5 min
- Design a image classification model on Azure Sphere - 5 min
- How to set up Azure Sphere - 5 min
- Exercise - Set up Azure Sphere - 5 min
- How to create a real time image classification application - 5 min
- Exercise - Create a real time image classification application - 5 min
- How to build a real time image classification application - 5 min
- Exercise - Build a real time image classification application - 5 min
- How to set up display output- 5 min
- Exercise - Set up display output - 5 min
- How to deploy a real time image classification application to Azure Sphere - 5 min
- Exercise - Deploy a real time image classification application to Azure Sphere - 5 min
- Knowledge check -5 min
- Summary - 3 min