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Scientific computing, machine learning and computer vision for .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 is compatible with the .NET Framework. NET Standard, .NET Core, and Mono.
a dbms for neural nets. Chatbots, DTrees, random forests, n-grams,...
This project consists out of a windows based designer application and a library (that can run on multiple platforms, including android) together with several demo applications (including an MVC3 chatbot client and an android application).
It is probably best compared to a database management system, but for neural networks instead of relational data. As such, the library is optimized for handling any type of data-size by using advanced streaming and caching algorithms.
With the designer,...
Fast Artificial Neural Network Library is a free open source neural network library, which implements multilayer artificial neural networks in C with support for both fully connected and sparsely connected networks. Cross-platform execution in both fixed and floating point are supported. It includes a framework for easy handling of training data sets. It is easy to use, versatile, well documented, and fast. Bindings to more than 15 programming languages are available. An easy to read...
NeuronDotNet is a neural network engine written in C#. It provides an interface for advanced AI programmers to design various types of artificial neural networks and use them.
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NxNet is an implementation of a BPN neural network written in C#. NxNet allows the user to configure the neural net, train and query the trained net. NxNet 2.0 introduces a batch query capability. Requires .Net Framework 2.0 be installed also.
DANNU - Database Artificial Neural Network Utility. A C#/.NET utility implementing the "NeuroBox" library which allows the user to import data from a database and train a network with it. A fully featured NN utlitility is envisioned.