Machine Learning for .NET by dotnet

ML.NET 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, 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. Build your first ML.NET model by following our ML.NET Getting Started tutorial. Check out our documentation and tutorials. See the API Reference documentation. Clone our [ML.NET Samples GitHub repo](https://github.com/dotnet/machinelearning-samples