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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.
Java class libraries for structural biology development: includes protein format conversion tool, printf-based text formatting, Pred2ary secondary structure prediction, neuralnet library, Hooke-Jeeves global optimizer, and misc. math & statistics.
By using a neuralnet from neuroph.org with the programmlanguage Java, you can change the net by this software.
Easy watch it on the screen and move the values up or down. More or less value at the output neurons.
Saving, Loading from different .nnet`s.
Adding comments.
Changing the visible output neuron
Setting wished input neurons to get visible.
A small fast and easy weight version and a continuing version, which should get involved in the neuroph project.
ANT is a lightweight implementation in C of a kind of artificial neuralnet called Multilayer Perceptron, which uses the backpropagation algorithm as learning method. The package includes an introductory example to start using artificial neural nets.
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‘intelliworm’ is a prototype simulation of a Intelligent Species of a common earth worm,which inherits human like decision making capabilities through Neural Network intelligence representation,all developed by integrating .NET with Lisp and Yacc.
The aim of GUINNEA (Graphical User Interfaced Neural Network Architecture) is to develop a comfortable and high-featured neuralnet simulator which is highly configurable and flexible. It will support many neural nets and visualization features for those
Jannis stands for "J Artificial NeuralNet Interactive Simulator".
Jannis' primary purpose is simulation of neuralnet models for scientific experiments in special-needs-education and neuropsychology.
neuralnetgen is intended to be a universal neuralnet generator that receives a neuralnet description (on NeuralNet Description Language, also developed on this project) and generates ANSI C code of a library that implements it.
Net.py is a tool for learning about neural nets. Currently, it only allows the user to experiment with a Hopfield net. I am now extending it to cover the Kohonen net. I'd be pleased to receive suggestions and criticism.