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ML.NET is a cross-platform open-source machine learning framework that makes machine learning accessible to .NET developers. In this GitHub repo, we provide samples that will help you get started with ML.NET and how to infuse ML into existing and new .NET apps. We're working on simplifying ML.NET usage with additional technologies that automate the creation of the model for you so you don't need to write the code by yourself to train a model, you simply need to provide your datasets. The "best" model and the code for running it will be generated for you. The ML.NET CLI (command-line interface) is a tool you can run on any command prompt (Windows, Mac or Linux) for generating good quality ML.NET models based on training datasets you provide. In addition, it also generates sample C# code to run/score that model plus the C# code that was used to create/train it so you can research what algorithm and settings it is using.
Features
- Supported on Windows, Linux, and macOS
- An open source and cross-platform machine learning framework
- ML.NET offers AutoML and productive tools to help you easily build, train, and deploy high-quality custom ML models
- ML.NET allows you to leverage other popular ML libraries like Infer.NET, TensorFlow, and ONNX for additional ML scenarios
- Use the same ML framework used by recognized Microsoft products like Power BI, Microsoft Defender, Outlook, and Bing
- With ML.NET, you can use your existing .NET skills to easily integrate ML into your .NET apps without any prior ML experience
Project Samples
