What is machinelearning-samples?

This repository is a collection of sample projects that show how to use ML.NET, Microsoft's machine learning framework for the .NET ecosystem. ML.NET lets C# and F# developers add AI-powered features to their applications without switching to Python or another language. The samples are organized into two types. The first type is simple console applications that each demonstrate one specific machine learning task, meant to help a developer understand how a particular technique works. The second type is complete end-to-end applications with web or desktop user interfaces, showing how a trained model fits into a real product. The scenarios covered include sentiment analysis (deciding whether a piece of text is positive or negative), spam detection, credit card fraud detection, price prediction, sales forecasting, product and movie recommendations, image classification, object detection, handwriting recognition, and more. Each sample comes with the code needed to load data, train a model, and make predictions. The samples are written for .NET developers who are new to machine learning and want a practical starting point using tools and languages they already know. Most samples are provided in both C# and F#. No prior machine learning experience is assumed, though familiarity with .NET development is expected. This repository holds only the sample code. If you encounter a bug in the ML.NET framework itself rather than in a sample, the project README directs you to file the issue in the main ML.NET repository instead.