Library for creating scientific computing, machine learning and pattern recognition applications.
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Accord.NET is a framework for scientific computing in .NET. The framework builds upon the popular AForge.NET Framework, focusing on providing statistical methods, machine learning, pattern recognition, audio processing and computer vision algorithms.
This framework is written completely in .NET and is not simply a wrapper around native libraries. I offers an extensive list of examples and sample applications to get the user up-and-running with the framework in no time. Source code is readily available and it be used in commercial applications with minor restrictions.
Developers and researchers on computer vision, machine learning and pattern recognition.