ML.NET is a free, cross-platform and open source machine learning framework designed to bring the power of machine learning into .NET applications. In this session we explore the capabilities, pitfalls, and alternatives of running full machine learning scenarios on your local .NET stack: from defining and training a model, to evaluating, deploying, and eventually running it.
Diederik Krols is a principal consultant for U2U Consult. He leads, designs and develops software applications that rely on new or upcoming Microsoft technologies. In his 25-years career he delivered enterprise-wide mission critical projects in the military, financial, medical, and industrial world. Diederik runs the popular XAMLBrewer blog. He is a Windows Development MVP since 2014.