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Neural Network Basic contain implementation of simple and effective implementation of neural network. Functionality it is developed in C++ native programming language, with use STL and Visual Studio C++ Express 2010.

http://neuralnetworkbasic.codeplex.com/Tags | neural-network neural-networks |

Implementation | C++ |

License | GPLv2 |

Platform | Windows |

ConvNetJS is a Javascript implementation of Neural networks, It currently supports Common Neural Network modules, Classification (SVM/Softmax) and Regression (L2) cost functions, A MagicNet class for fully automatic neural network learning (automatic hyperparameter search and cross-validatations), Ability to specify and train Convolutional Networks that process images, An experimental Reinforcement Learning module, based on Deep Q Learning.

artificial-intelligence neural-networks machine-learning deep-learningFast 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 intro

RSNNS: Neural Networks in R using the Stuttgart Neural Network Simulator (SNNS)

This is simple Back-Propagation Neural Network simulation using C#. This code is a part of my "Supervised Neural Network" book written in 2006.

neural-networkRecent results in Bayesian statistics for constructing robust neural networks have proved that it is one of the best ways to deal with uncertainty, overfitting but still having good performance. Gelato will help to use bayes for neural networks. Library heavily relies on Theano, Lasagne and PyMC3.I use generic approach for decorating all Lasagne at once. Thus, for using Gelato you need to replace import statements for layers only. For constructing a network you need to be the in pm.Model context environment.

bayesian-inference lasagne uncertainty variational-inference gelato neural-network theano deep-learning bayesianCluster Networks are a new style of neural simulation / neural network modeling, that models networks of neural populations (quot;clustersquot;) that transform and transmit information using precisely-timed, graded bursts (quot;pulsesquot; or quot;volleysquot;) of firing.

nn-utility is a neural network library for C++ and Java. Its aim is to simplify the tedious programming of neural networks, while allowing programmers to have maximum flexibility in terms of defining functions and network topology.

The Microsoft Cognitive Toolkit is a free, easy-to-use, open-source, commercial-grade toolkit that trains deep learning algorithms to learn like the human brain. It is a unified deep-learning toolkit that describes neural networks as a series of computational steps via a directed graph.

deep-learning neural-networks artificial-intelligencePlaying with neural networks and AD in haskell.

A (relatively) simple feed-forward neural network in NumPy/Cython. Only basic layers for multi-layer perceptrons and convolutional neural networks are implemented.

Evolving of neural networks for collective agents

Lopez, R. (2010). Flood: An Open Source Neural Networks C++ Library (Version 3) [software]. Retrieved from http://www.cimne.com/flood Flood is a comprehensive implementation of the multilayer perceptron neural network in the C++ programming language. It includes several objective functionals and training algorithms, as well as different utilities for the solution of a wide range of problems. Flood also provides an effective framework for the research and development of neural networks algorith

Exercises for the course T-61.5130 Machine Learning and Neural Networks

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.

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.

machine-learning framework c-sharp nuget visual-studio statistics unity3d neural-network support-vector-machines computer-vision image-processing ffmpegCURRENTLY NOT WORKING! There will be a further notice when it's updated.NEAT (NeuroEvolution of Augmenting Topologies) is a neuroevolution algorithm by Dr. Kenneth O. Stanley which evolves not only neural networks' weights but also their topologies. This method starts the evolution process with genomes with minimal structure, then complexifies the structure of each genome as it progresses. You can read the original paper from here.

neat neuroevolution neural-network topologies reinforcement-learning recurrent-neural-networks genetic-algorithm machine-learning go-libraryNEUGO is a simple neural networks framework in Go, which allows the users to easily customize a neural network by adding/removing nodes (neurons) and connections, therefore providing intuitive interfaces and flexible topologies. The framework is still in development.Following are available algorithms currently. More will be added with further updates.

PyTorch is a deep learning framework that puts Python first. It is a python package that provides Tensor computation (like numpy) with strong GPU acceleration, Deep Neural Networks built on a tape-based autograd system. You can reuse your favorite python packages such as numpy, scipy and Cython to extend PyTorch when needed.

neural-network autograd gpu numpy deep-learning tensorAmygdala is a C++ spiking neural network library. It includes several neuron models, SMP support and facilities for developing SNNs with genetic algorithms. Support for running Amygdala neural networks on workstation clusters and MPPs is also under way

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