Accord.NETaccord-net/framework Archived
Together with AForge.NET, this library can provide image processing and computer vision algorithms to Windows, Windows RT and Windows Phone. Some components are also available for Java and Android.

aforgenet.com
Open source C# framework for developers and researchers in the fields of Computer Vision and Artificial Intelligence. Development has now shifted to GitHub.
Together with AForge.NET, this library can provide image processing and computer vision algorithms to Windows, Windows RT and Windows Phone. Some components are also available for Java and Android.
Cross platform wrapper of OpenCV which can be compiled in Mono to be run on Windows, Linus, Mac OS X, iOS, and Android.
.NET Standard bindings for Apache MxNet with Imperative, Symbolic and Gluon Interface for developing, training and deploying Machine Learning models in C#. https://mxnet.tech-quantum.com/
ML.NET is a cross-platform open-source machine learning framework which makes machine learning accessible to.NET developers. ML.NET was originally developed in Microsoft Research and evolved into a significant framework over the last decade and is used across many product groups in Microsoft like Windows, Bing, PowerPoint, Excel and more.
Numerical foundation of the Math.NET project, aiming to provide methods and algorithms for numerical computations in science, engineering and everyday use. Supports.Net 4.0,.Net 3.5 and Mono on Windows, Linux and Mac; Silverlight 5, WindowsPhone/SL 8, WindowsPhone 8.1 and Windows 8 with PCL Portable Profiles 47 and 344; Android/iOS with Xamarin.
Infer.NET is a framework for running Bayesian inference in graphical models. One can use Infer.NET to solve many different kinds of machine learning problems, from standard problems like classification, recommendation or clustering through customized solutions to domain-specific problems. Infer.NET has been used in a wide variety of domains including information retrieval, bioinformatics, epidemiology, vision, and many others.
Multi-platform genetic algorithm library for.NET Core and.NET Framework. The library has several implementations of GA operators, like: selection, crossover, mutation, reinsertion and termination.