Windows ML

Transform your Windows application with the power of artificial intelligence. Windows ML empowers you and your business to achieve more by providing intelligent solutions to complex problems.

Windows Machine Learning (WinML)

Overview

• Overview of Windows Machine Learning

Concept

• What is a machine learning model?
• Working with ONNX models
• Windows ML performance and memory
• Executing multiple ML models in a chain

Tutorial

• Image classification with Custom Vision and Windows Machine Learning
• Image Classification with ML.NET and Windows Machine Learning
• Image classification with PyTorch and Windows Machine Learning
• Data analysis with PyTorch and Windows Machine Learning
• Object detection with TensorFlow and Windows Machine Learning
• Create a basic WinML UWP app (C#)
• Create a basic WinML UWP app (C++)
• Convert trained models to ONNX

Reference

• API Reference
• Core APIs (Windows.AI.MachineLearning Namespace)
• Custom operators
• WinML native APIs
• Tools and Samples
• Release Notes
• Frequently Asked Questions

Direct Machine-Learning (DirectML)

Overview

• Overview of DirectML
• GPU accelerated ML training in WSL

Concept

• Binding in DirectML
• UAV barriers and resource state barriers
• Using strides to express padding, memory layout
• Resource lifetime and synchronization
• Using the debug layer
• Handling errors and device-removal
• Helper functions

Reference

• DirectML reference
• Sample applications