machinelearning-samples

Why we included this project

This is the official set of runnable ML.NET examples, aimed at .NET developers who want to actually use machine learning instead of just reading about it. Each classic task, from sentiment and spam classification to fraud detection, regression, clustering, recommendation, ranking, and time-series forecasting, comes as a small console app you can open, build, and step through in C# or F#. The end-to-end samples go further and show how to wrap a trained model in a Web API, a Razor or Blazor app, or an Azure Function, the part tutorials usually skip. Beyond the hand-written samples, the repo also demonstrates the ML.NET CLI and the AutoML API, so you can see how automated model generation works before adopting it. If you're standardizing on .NET, these examples are a direct route from a working sample to your own pipeline.