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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 ffmpegGorgonia is a library that helps facilitate machine learning in Go. Write and evaluate mathematical equations involving multidimensional arrays easily. If this sounds like Theano or TensorFlow, it's because the idea is quite similar. Specifically, the library is pretty low-level, like Theano, but has higher goals like Tensorflow.The main reason to use Gorgonia is developer comfort. If you're using a Go stack extensively, now you have access to the ability to create production-ready machine learning systems in an environment that you are already familiar and comfortable with.

machine-learning artificial-intelligence neural-network computation-graph differentiation gradient-descent gorgonia deep-learning deeplearning deep-neural-networks automatic-differentiation symbolic-differentiation go-libraryA general-purpose encoder-decoder framework for Tensorflow that can be used for Machine Translation, Text Summarization, Conversational Modeling, Image Captioning, and more.The official code used for the Massive Exploration of Neural Machine Translation Architectures paper.

tensorflow translation machine-translation neural-network deeplearningTheano is a Python library that allows you to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays. It is built on top of NumPy. Its features include tight integration with NumPy, transparent use of a GPU, dynamic C code generation and lot more.

deep-learning neural-network math numerical symbolic blas numpy gpu autodiff differentiationThe OpenCog Framework is a platform to build and share artificial intelligence programs. It includes components for procedural and declarative knowledge representation (AtomSpace), task scheduling (CogServer), AI algorithm containers (MindAgents), connectors to instant messaging and virtual world systems, and other components. MindAgents and other add-ons explore a wide variety of AI techniques including evolutionary program learning (MOSES), natural language processing, and others.

artificial-intelligence neural-network nlpDeeplearning4J is an open source, distributed neural net library written in Java and Scala. It integrates with Hadoop and Spark and runs on several backends that enable use of CPUs and GPUs. It provides versatile n-dimensional array class for Java and Scala.

deep-learning neural-network numerical scientific artificial-intelligenceMulti Touch Digit OCR Project is a wpf project that works on multi touch devices but it works well on normal devices , this project uses matlab core , that creates 4 feed forward neural network and train them with Back Propagation Algorithm for detecting numbers that you draw .

backpropagation com-library machine-learning matlab multitouch neural-networkDigit recognition contain implementation of simple and effective implementation of neural network. Neural network is used to recognize handwritten digits - OCR system. Core functionality it is developed in C++ native programming language, STL, boost, GUI in C++ .NET.

neural-network ocr recognitionNeural 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.

neural-network neural-networksThis project is my magistracy resulting work. It is intended to be an example of using neural networks in cryptography. Hashing functions are chosen as the first step in this broad topic. Implementation language is F# running under .NET 4.0 with VS 2010 RC

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

neural-networkCURRENTLY 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-libraryRecent 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 bayesianThis is a simple neural network built in Go. It is further discussed here and in Machine Learning with Go.

neural-network data-science artificial-intelligence machine-learning code-samples