/Windows-Machine-Learning

Samples for Windows ML.

MIT LicenseMIT

Windows ML samples

This repo contains sample apps that demonstrate how to use Windows ML to build machine learning applications for Windows 10.

For tutorials, how-tos, and additional information, see the Windows ML documentation: https://docs.microsoft.com/windows/uwp/machine-learning

Sample apps

These generic examples show how to use various models and input feeds with Windows ML.

  • MNIST: Uses the MNIST model to recognize a numeric digit drawn by the user.
  • SqueezeNet: Uses the SqueezeNet model to detect the predominant object in an image.
  • WinMLExplorer: Uses a circuit board defect detection model to detect defects from images or a real-time camera feed.

Requirements

Contributing

We're always looking for your help to fix bugs and improve the samples. Create a pull request, and we'll be happy to take a look.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.