machinelearning

ML.NET is Microsoft's open-source machine learning framework for .NET developers. Machine learning is the practice of training software on example data so it can make predictions or find patterns on new data, and ML.NET brings that capability to developers who already work in C#, F#, or other .NET languages without requiring them to switch to Python or R.

The library covers common machine learning tasks such as classification (sorting items into categories), forecasting (predicting future values from historical data), and anomaly detection (spotting unusual patterns). It handles loading data from files and databases, transforming it into a form the algorithms can use, and training the model. Once trained, a model can be saved and loaded back into a production application.

ML.NET also supports loading models created with TensorFlow and ONNX, two widely used formats from other machine learning ecosystems. This means a team could train a model using other tools and then run it inside a .NET application using ML.NET as the runtime.

Adding the library to a project is a single command: dotnet add package Microsoft.ML. From there, developers write C# code to define a data pipeline, train a model, and call it with new inputs. Microsoft provides tutorials, sample projects, and a getting-started guide aimed at developers with no prior machine learning experience.

The framework runs on Windows, Linux, and macOS, and supports ARM64 processors including Apple M1 chips. It works with both modern .NET Core and the older .NET Framework. The project is actively maintained by Microsoft and is free and open source.