dotnet/machinelearning

Health v2 · maintenance only

Adoption not part of the score

9351 stars · 1950 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

ML.NET is an open-source, cross-platform machine learning framework for .NET that lets developers build, train, and deploy custom ML models using C# or F#. It includes data loading and transformation pipelines, many ML algorithms, AutoML support, and can consume TensorFlow and ONNX models.

Use cases

• train a classification model in C#
• add machine learning to a .NET application without Python
• detect anomalies in time series data
• run TensorFlow or ONNX models in .NET
• build a sentiment analysis model
• forecast values with .NET
• use AutoML to train models from .NET code

When to choose

• you are a .NET developer wanting ML without learning Python
• you need to embed trained models directly in C#/F# applications
• you want cross-platform ML on Windows, Linux, and macOS including ARM64
• you need to consume TensorFlow or ONNX models within .NET

When to avoid

• you need cutting-edge deep learning research tooling or large model training
• your team primarily works in Python with PyTorch or scikit-learn
• you need the broadest ecosystem of pretrained models and community libraries

Facets

framework · maturity active

machine-learning data-science etl machine-learning data-science cross-platform windows dotnet cross-platform mlnet automl onnx tensorflow csharp classification anomaly-detection forecasting linux macos

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markdown · JSON · MCP: product_card(name="dotnet/machinelearning")