ML.NET is brilliant for doing Machine Learning in .NET!

But is the framework really mature enough for a full-fledged Data Science project? How do we work with models trained on 1000+ features? How do I make sense of the data, and how can I create simple and intuitive visualizations? What about quickly prototyping a solution that you can share with a co-worker?

The questions are many.

In this session will explore the new C# kernel for Jupyter Notebooks, and look at the newly released DataFrame type to see how these can help us solve our problems. This session will teach you how you can use C# and .NET for the end-to-end machine learning process.