Accord.NET Framework

Machine learning made in a minute
The Accord.NET Framework is a .NET machine learning framework combined with audio and image processing libraries completely written in C#. It is a complete framework for building production-grade computer vision, computer audition, signal processing and statistics applications even for commercial use. A comprehensive set of sample applications provide a fast start to get up and running quickly, and an extensive documentation and wiki helps fill in the details.

[Accord.NET Framework]

NET Machine Learning: F# and Accord.NET

Alena Hall. InfoQ.
Alena Hall presents various machine learning algorithms available in Accord.NET – a framework for machine learning and scientific computing in .NET. Hall also takes a look at sample types of problems to see how we can apply machine learning algorithms using the Accord.NET framework with the F# functional approach.