ML.NET is an open-source framework for machine learning that is available for .NET developers (C# / F#) that allows you to train, build and deploy ML models for several scenarios: sentiment analysis, value prediction, even image classification. The models can be saved and consumed from other applications (web, desktop, mobile).

To accomplish this ML.NET accepts data that comes from files, in-memory lists and also, databases.

In this session, I'll explain what is ML.NET and how to build a ML model from data that is stored in an Azure SQL database. The connection will be made through Model Builder (integrated in Visual Studio) and also from C# code (thanks to the ML.NET API).