Top 20 NuGet artificial Packages

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Contains Support Vector Machines, Decision Trees, Naive Bayesian models, K-means, Gaussian Mixture models and general algorithms such as Ransac, Cross-validation and Grid-Search for machine-learning applications. This package is part of the Accord.NET Framework.
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This package contains libraries of the Accord.NET Framework that are NOT available under the LGPL. It currently includes Accord.MachineLearning.GPL, which contains GPL code and thus can only be used inside GPL-compliant applications. Please take extra care before including this library in your proje...
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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.
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AIStudio is a desktop “AI Editor” application for designers and developers. It enables the rapid creation, deployment and management of complex personality based AI conversations. The AIStudio Adapter for Microsoft Bot Framework enables you to quickly build, test and deploy a bot directly into a Bot...
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AIStudio is a desktop “AI Editor” application for designers and developers. It enables the rapid creation, deployment and management of complex personality based AI conversations. The AIStudio Adapter for WPF enables you to quickly build, test and deploy an AI host directly into a .Net solution that...
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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.
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a .net implementation of aima.
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A library for serializing/deserializing neural networks created with SodiumPlus
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A library for training neural networks created with SodiumPlus
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A simple neural network implementation in .NET / C#
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A powerful neural network library for creating perceptron for classifying inputs. Also see SodiumPlusTraining for training neural networks using the error backpropagation approach.