Top 20 NuGet learning Packages

Microsoft Cognitive Toolkit Libraries, CPU-Only Build
Microsoft Cognitive Toolkit Libraries, GPU Build
Extreme Optimization Numerical Libraries for .NET Single-Precision P/Invoke MKL Provider for Linux.
Extreme Optimization Numerical Libraries for .NET P/Invoke MKL Provider for Linux.
The Extreme Optimization Numerical Libraries for .NET are a set of libraries for numerical computing and data analysis. This is the main package that contains all the core functionality. For optimal performance, we recommend also referencing one of the native packages based on Intel's Math Kernel ...
Microsoft.ML.TensorFlow.Redist contains the TensorFlow C library version 1.10.0 redistributed as a NuGet package.
This package contains Microsoft's implementation of ONNX runtime, usable in .Net platforms
A complete C# re-write of Berkeley's open source Convolutional Architecture for Fast Feature Encoding (CAFFE) for Windows C# Developers, now with Policy Gradient Reinforcement Learning, cuDNN LSTM Recurrent Learning, and Neural Style Transfer support!
Official Vowpal Wabbit library including C# interface
ML.NET is a cross-platform open-source machine learning framework which makes machine learning accessible to .NET developers.
FsLab is a combination package that supports doing data science with F#. FsLab includes literate scripting converted to HTML and PDF, and by default references Deedle (a data frame library), FSharp.Data (for data access) and XPlot (for visualization). You can optionally add any other nuget packages.
Provides learning algorithms and models for XGBoost regression and classification.
Provides cross-validation, training/test set samplers and learning curves for SharpLearning.
Provides learning algorithms and models for DecisionTree regression and classification.
Provides ensemble learning for regression and classification.
Provides learning algorithms and models for GradientBoost regression and classification.
Provides learning algorithms and models for neural net regression and classification.
Provides optimization algorithms.
Provides learning algorithms and models for RandomForest and ExtraTrees regression and classification.
The core of the Accord.NET Framework. Contains basic classes such as general exceptions and extensions used by other framework libraries.