ML.NET is a free, cross-platform, and open-source machine learning framework built for .NET developers. This ML framework provides tools and features to help .NET developers easily build, train, deploy, and consume high-quality custom machine learning models both locally and in Azure, without leaving the .NET ecosystem and without requiring prior machine learning experience. This session focuses on the basic framework components and use cases of ML.NET and through a variety of demos describes how to build custom ML models like sentiment analysis, image classification, and recommender systems from scratch, using both the API and Visual Studio tooling with AutoML support. This session is a great way to get a jump start with Machine Learning using ML.NET!

You will learn:
• About ML.NET and how it works
• What kind of machine learning scenarios are supported in ML.NET
• How to build a machine learning model with ML.NET
• How ML.NET is being used in the real world
• What's coming up next in the ML.NET roadmap