The AForge.Neuro library contains classes for artificial neural network computation - feed forwards networks with error back propagation learning and Kohonen self organizing maps. Full list of features is available on the project's web site.
Encog is an advanced machine learning framework that supports a variety of advanced algorithms, as well as support classes to normalize and process data. Machine learning algorithms such as Support Vector Machines, Artificial Neural Networks, Genetic Programming, Bayesian Networks, Hidden Markov...
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Deep learning library for F#. Provides symbolic model differentiation, automatic differentiation and compilation to CUDA GPUs. Includes optimizers and model blocks used in deep learning.
Make sure to set the platform of your project to x64.
Contains neural learning algorithms such as Levenberg-Marquardt, Parallel Resilient Backpropagation, initialization procedures such as Nguyen-Widrow and other neural network related methods. This package is part of the Accord.NET Framework.
Catalyst is a Natural Language Processing library built from scratch for speed. Inspired by spaCy's design, it brings pre-trained models, out-of-the box support for training word and document embeddings, and flexible entity recognition models. You can install language-specific models with the model...
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Bright Wire is an open source machine learning library. Includes neural networks (feed forward, convolutional and recurrent), naive bayes, linear regression, decision trees, logistic regression, k-means clustering and dimensionality reduction.
.NET Bindings for Torch. Requires reference to one of libtorch-cpu, libtorch-cuda-11.3, libtorch-cuda-11.3-win-x64 or libtorch-cuda-11.3-linux-x64 version 1.10.0.1 to execute.
Parallel Neural Network Classes for .NET. Backpropagation class for easy training and testing.
Code Project link:
http://www.codeproject.com/Articles/1016734/Parallel-Artificial-Neural-Networks-in-NET-Frame
GitHub link:
https://github.com/hemanthk119/NeuralNetworks/