Top 20 NuGet neural Packages

Developing a C# wrapper to help developer easily create and train deep neural network models. Easy to use library, just focus on research Multiple backend - ArrayFire (In Progress), TensorSharp (In Progress), CNTK (Not Started), TensorFlow (Not Started), MxNet (Not Started) CUDA/ OpenCL support for...
Text Analytics and Sentiment Analysis API - allows to perform following: Sentiment analysis, Document classification, Entity extraction, Themes discovery, Keyword analysis, Citation detection, Slang detection..
DyNet is a neural network library developed by Carnegie Mellon University and many others. It is written in C++ (with bindings in Python and C#) and is designed to be efficient when run on either CPU or GPU, and to work well with networks that have dynamic structures that change for every training i...
Provides learning algorithms and models for neural net regression and classification.
This is a lightweight package which is able to run neural networks with weights from different sources like Keras models.
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.
Bright Wire CUDA adds GPU support to Bright Wire. This lets you run Bright Wire machine learning on a Maxwell or better NVIDIA GPU.
Package Description
TensorFlow backend for SiaNet library. Please install SiaNet along with this backend.
MxNet backend for SiaNet library. Please install SiaNet along with this backend.
CNTK backend for SiaNet library. Please install SiaNet along with this backend.
CNTK CPU Only backend for SiaNet library. Please install SiaNet along with this backend.
ArrayFire backend for SiaNet library. Please install SiaNet along with this backend.
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.
This is the .net standard 2 version of Bright Wire. Bright Wire is an open source machine learning library. Includes deep learning (feed forward, convolutional and recurrent), naive bayes, linear regression, decision trees, logistic regression, k-means clustering and dimensionality reduction.
This is the .net standard 2 version of BrightWire.CUDA which adds CUDA support to Bright Wire. This lets you run Bright Wire machine learning on a Maxwell or better NVIDIA GPU (x64 only).
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.
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.
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 Mod...
SharpNEAT - Evolution of Neural Networks.