machinelearning

# Machine Learning for .NET

[ML.NET](https://dotnet.microsoft.com/apps/machinelearning-ai/ml-dotnet) is a cross-platform open-source machine learning (ML) framework for .NET.

ML.NET allows developers to easily build, train, deploy, and consume custom models in their .NET applications without requiring prior expertise in developing machine learning models or experience with other programming languages like Python or R. The framework provides data loading from files and databases, enables data transformations, and includes many ML algorithms.

With ML.NET, you can train models for a [variety of scenarios](https://docs.microsoft.com/dotnet/machine-learning/resources/tasks), like classification, forecasting, and anomaly detection.

You can also consume both TensorFlow and ONNX models within ML.NET which makes the framework more extensible and expands the number of supported scenarios.

## Getting started with machine learning and ML.NET

- Learn more about the [basics of ML.NET](https://dotnet.microsoft.com/apps/machinelearning-ai/ml-dotnet).
- Build your first ML.NET model by following our [ML.NET Getting Started tutorial](https://dotnet.microsoft.com/learn/ml-dotnet/get-started-tutorial/intro).
- Check out our [documentation and tutorials](https://docs.microsoft.com/dotnet/machine-learning/).
- See the [API Reference documentation](https://docs.microsoft.com/dotnet/api/?view=ml-dotnet).
- Clone our [ML.NET Samples GitHub repo](https://github.com/dotnet/machinelearning-samples) and run some sample apps.
- Take a look at some [ML.NET Community Samples](https://github.com/dotnet/machinelearning-samples/blob/main/docs/COMMUNITY-SAMPLES.md).
- Watch some videos on the [ML.NET videos YouTube playlist](https://aka.ms/mlnetyoutube).

## Roadmap

Take a look at ML.NET's [Roadmap](ROADMAP.md) to see what the team plans to work on in the next year.

## Operating systems and processor architectures supported by ML.NET

ML.NET runs on Windows, Linux, and macOS using .NET, or Windows using .NET Framework.

ML.NET also runs on ARM64, Apple silicon, and Blazor WebAssembly. However, there are some [limitations](docs/project-docs/platform-limitations.md).

64-bit is supported on all platforms. 32-bit is supported on Windows, except for TensorFlow and LightGBM related functionality.

## ML.NET NuGet packages status

[![NuGet Status](https://img.shields.io/nuget/v/Microsoft.ML.svg?style=flat)](https://www.nuget.org/packages/Microsoft.ML/)

[![Latest NuGet Status](https://img.shields.io/nuget/vpre/Microsoft.ML.svg?style=flat)](https://www.nuget.org/packages/Microsoft.ML/absoluteLatest)

## Release notes

Check out the [release notes](docs/release-notes) to see what's new. You can also read the [blog posts](https://devblogs.microsoft.com/dotnet/category/ml-net/) for more details about each release.

## Using ML.NET packages

The main `Microsoft.ML` package targets [.NET Standard 2.0](https://learn.microsoft.com/dotnet/standard/net-standard), so it can be used by compa