Top 20 NuGet learning Packages
Google's TensorFlow full binding in .NET Standard. Building, training and infering deep learning models. https://tensorflownet.readthedocs.io
This package contains native shared library artifacts for all supported platforms of ONNX Runtime.
A complete C# re-write of Berkeley's open source Convolutional Architecture for Fast Feature Encoding (CAFFE) for Windows C# Developers with full On-line Help, now with Seq2Seq/Attention, Single-Shot MultiBox, TripletNet, SiameseNet, NoisyNet, Deep Q-Network and Policy Gradient Reinforcement Learnin...
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 strongly recommend also referencing one of the native packages based on Intel's Mat...
The core of the Accord.NET Framework. Contains basic classes such as general exceptions and extensions used by other framework libraries.
Microsoft.ML.Mkl.Redist contains the MKL library redistributed as a NuGet package.
ML.NET is a cross-platform open-source machine learning framework which makes machine learning accessible to .NET developers.
Keras for .NET Keras is an API designed for human beings, not machines. Keras follows best practices for reducing cognitive load: it offers consistent & simple APIs, it minimizes the number of user actions required for common use cases, and it provides clear & actionable error messages.
C# bindings for NumPy - a fundamental library for scientific computing, machine learning and AI. Does not require a local Python installation!
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.
Giving Windows C# developers easy access to the ONNX AI Model Format for easy model conversions.
C# bindings for NumPy on Win64 - a fundamental library for scientific computing, machine learning and AI. Does require Python 3.8 with NumPy 1.16 installed!
Contains the IDataView system which is a set of interfaces and components that provide efficient, compositional processing of schematized data for machine learning and advanced analytics applications.