ML.NET Documentation

Learn how to use ML.NET, an open-source and cross-platform machine learning framework for building custom machine learning solutions and integrating them into .NET applications. Tutorials, code examples, API reference, and other documentation show you how.

Get Started

To learn how a machine learning application is built with ML.NET, read What is ML.NET and how does it work? Or get started by adding the Microsoft.ML NuGet package to your application.

Step-by-Step Tutorials

Learn how to create common solutions with ML.NET:

Reference and Resources

The ML.NET API has two sets of packages: release components and preview components. The release API contains components for data handling, algorithms for binary classification, multiclass classification, regression, anomaly detection, time series and forecasting, ranking, model saving and loading, ONNX and TensorFlow model handling, and much more! The preview API contains algorithms for recommendation tasks, and support for standard deep learning models.