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Machine learning, computer vision, statistics and general scientific computing for .NET
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README.md

The Accord.NET Framework http://accord-framework.net

The Accord.NET Framework provides machine learning, mathematics, statistics, computer vision, computer audition, and several scientific computing related methods and techniques to .NET. The project extends the popular AForge.NET Framework providing a more complete scientific computing environment.

The GitHub repository at https://github.com/accord-net/framework is the official home of the project after release 2.10 was finished. As such, new releases will only be made available on this repository.

Installing the framework


1) Download the framework through NuGet: https://www.nuget.org/packages?q=accord.net

2) Follow the Getting Started Guide http://accord-framework.net/get-started.html

3) Check the sample applications and find one that is related to what you need. http://accord-framework.net/samples.html

If you have installed the framework using the installer, the samples will be at

 C:\Program Files (x86)\Accord.NET\Framework\Samples

You can open the Samples.sln solution on Visual Studio and check the sample applications for examples. Complete documentation is also available online at

 http://accord-framework.net/docs/Index.html

Building with Visual Studio


1) Clone the repository (SmartGit is the best Git tool available for Windows) 2) Open Sources/Accord.NET.sln in Visual Studio (works with Express versions)

Building in Linux with Mono


Install Mono

sudo apt-get install mono-complete monodevelop monodevelop-nunit

Clone the repository

git clone https://github.com/accord-net/framework.git

Enter the directory

cd framework

Build the framework solution using Mono

mdtool build -c:"NET40" Sources/Accord.NET.Mono.sln

Join the chat at https://gitter.im/accord-net/framework

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