112 packages returned for Tags:"machinelearning"

NumSharp is the fundamental library for scientific computing with .NET providing a similar API to python's numpy scientific library. NumSharp has full N-D, broadcasting and axis support. If you want to use .NET to get started with machine learning, NumSharp will be your best tool.

Amazon Machine Learning is a service that makes it easy for developers of all skill levels to use machine learning technology.

NumSharp.Lite is the compact version of NumSharp without full datatype supported.

Machine Learning library in .NET Core.

Provides learning algorithms and models for DecisionTree regression and classification.

Dlib wrapper library written in C++ and C# for Windows, MacOS and Linux Requirements: Visual C++ 2017 Redistributable Package

Redistributable components for package 'AWSSDKCPP-MachineLearning'. This package should only be installed as a dependency. (This is not the package you are looking for).

DirectML Redistributable Package.

Amazon Machine Learning Client for the AWS SDK for C++. AWS SDK for C++ provides a modern C++ (version C++ 11 or later) interface for Amazon Web Services (AWS). It is meant to be performant and fully functioning with low- and high-level SDKs, while minimizing dependencies and providing platform... More information

This is a C# class library containing some very basic geodesic algorithms. It is based on work by Mike Gavaghan and has been enhanced by me to cover also some variants of Mercators projection of the earth to flat maps. I cover Spherical and Elliptical Mercator projections, mapping the earth to a... More information

Provides learning algorithms and models for RandomForest and ExtraTrees regression and classification.

Provides classification, regression, impurity and ranking metrics.

Dlib wrapper library written in C++ and C# for Windows, MacOS and Linux Requirements: Visual C++ 2017 Redistributable Package, cublas64_92.dll, cudnn64_7.dll, curand64_92.dll and cusolver64_92.dll

Provides learning algorithms and models for GradientBoost regression and classification.

The world's simplest facial recognition api for .NET This library is ported from https://github.com/ageitgey/face_recognition by C#.

Provides ensemble learning for regression and classification.

Provides optimization algorithms.

Utilize ML5 Library from c# in Blazor Client.Play with Teachable Machine models or Create a Neural Network model or use a Image Classifier or Sound Classifier or YOLO or COCOSSD model or PoseNet model , visit Github for documentation.

Provides learning algorithms and models for AdaBoost regression and classification.

An easy and quick way to use libsvm in your .NET projects. Envoy !