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

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Accord.NET Framework

Build Status Github All Releases License NuGet NuGet Pre Release

The Accord.NET project provides machine learning, statistics, artificial intelligence, computer vision and image processing methods to .NET. It can be used on Microsoft Windows, Xamarin, Unity3D, Windows Store applications, Linux or mobile.

After merging with the AForge.NET project, the framework now offers a unified API for learning/training machine learning models that is both easy to use and extensible. It is based on the following pattern:

For more information, please see the getting started guide, and check the wiki. Note: the wiki is being gradually updated/rewritten followed the recent merge/refactoring. Please do not hesitate to edit it if you would like!

Installing

To install the framework in your application, please use NuGet. If you are on Visual Studio, right-click on the "References" item in your solution folder, and select "Manage NuGet Packages." Search for Accord.MachineLearning (or equivalently, Accord.Math, Accord.Statistics or Accord.Imaging depending on your initial goal) and select "Install."

If you would like to install the framework on Unity3D applications, download the "libsonly" compressed archive from the framework releases page. Navigate to the Releases/Mono folder, and copy the .dll files to the Plugins folder in your Unity project. Finally, find and add the System.ComponentModel.DataAnnotations.dll assembly that should be available from your system to the Plugin folders as well.

Sample applications

The framework comes with a wide range of sample applications to help get you started quickly. If you downloaded the framework sources or cloned the repository, open the Samples.sln solution file in the Samples folder.

Building

With Visual Studio 2013

Please download and install the following dependencies:

Then navigate to the Sources directory, and open the Accord.NET.sln solution file.

With Visual Studio 2015

Please download and install the following dependencies:

Then navigate to the Sources directory, and open the Accord.NET.sln solution file.

With Visual Studio 2017

Please download and install the following dependencies:

Then navigate to the Sources directory, and open the Accord.NET.sln solution file.

With Mono (Linux/xbuild)

# Install Mono
sudo apt-get install mono-complete monodevelop monodevelop-nunit git autoconf make

# Clone the repository
git clone https://github.com/accord-net/framework.git

# Enter the directory
cd framework

# Build the framework solution using Mono
./autogen.sh
make build
make samples
make test

Contributing

If you would like to contribute, please do so by helping us update the project's Wiki pages. While you could also make a donation through PayPal Donate or Flattr Flattr this git repo, fill-in bug reports and contribute code in the form of pull requests, the most precious donation we could receive would be a bit of your time - please take some minutes to submit us more documentation examples to our Wiki pages 😉

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

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

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