dotnet/machinelearning

ML.NET is an open source and cross-platform machine learning framework for .NET.

What it solves

ML.NET is a cross-platform open-source machine learning framework designed to let .NET developers build, train, and deploy custom ML models without needing to learn Python or R or have deep prior expertise in machine learning development.

How it works

The framework provides a complete pipeline for machine learning, including data loading from files and databases, data transformations, and a variety of built-in ML algorithms. It also supports the consumption of external models created in TensorFlow and ONNX formats, making it more extensible.

Who it’s for

It is primarily for .NET developers who want to integrate machine learning capabilities into their applications across Windows, Linux, and macOS, as well as ARM64, Apple M1, and Blazor Web Assembly.

Highlights

  • own built-in algorithms for classification, forecasting, and anomaly detection
  • Support for TensorFlow and ONNX models
  • Cross-platform compatibility (Windows, Linux, macOS)
  • Integrated data loading and transformation tools

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