Found 2,347 packages
Enrich Serilog log events with properties from System.Environment.
Machine.Specifications is a Context/Specification framework geared towards removing language noise and simplifying tests.
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.
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.
Machine.Specifications.Should is a should library for the Context/Specification framework Machine.Specifications
ML.NET is a cross-platform open-source machine learning framework which makes machine learning accessible to .NET developers.
Machine.Specifications (MSpec) adapter for .NET Framework and .NET Core including dotnet cli (dotnet test), Visual Studio IDE, TFS, Visual Studio Online, Visual Studio Team Services.
Provides Graph RBAC management (Fluent) capabilities for Microsoft Azure. This package is in low maintenance mode and being phased out. To use the latest Azure SDK for resource management, please see https://aka.ms/azsdk/dotnet/mgmt
Hierarchical state machine with fluent definition syntax Features: states and events can be defined with enums, strings or ints - resulting in single class state machines, actions on transitions, entry and exit actions, transition guards, hierarchical with different history behaviors to initialize state always to same state or last active state, fluent definition interface, synchronous/asynchronous state machine (passive state machine handles state transitions synchronously, active state machine handles state transitions asynchronously on the worker thread of the state machine), extensible thorough logging, state machine report for description of state machine (csv, yEd)
Microsoft.ML.CpuMath contains optimized math routines for ML.NET.
Console runner for the Context/Specification framework Machine.Specifications
Machine.Fakes attempts to simplify the usage of such frameworks on top of Machine.Specifications by helping to reduce a lot of the typical fake framwork related clutter code in specifications. If you choose so, Machine.Fakes even helps you to stay mostly independent of a concrete fake framework by providing a little wrapper API and a provider model for fake frameworks.
This package contains ONNX Runtime for .Net platforms
Amazon Machine Learning is a service that makes it easy for developers of all skill levels to use machine learning technology.
This package contains native shared library artifacts for all supported platforms of ONNX Runtime.
ML.NET component for LightGBM
RazorMachine is a robust Razor 2.0/3.0 templating engine that supports layouts as well as a _viewStart construct like Asp.Net MVC
The core of the Accord.NET Framework. Contains basic classes such as general exceptions and extensions used by other framework libraries.
Microsoft.ML.Tokenizers contains the implmentation of the tokenization used in the NLP transforms.
ML.NET component for FastTree