Microsoft recently launched ML.NET 1.1 which is a great entry point for .NET developers and to gain experience building something with Machine Learning.
With the recent release of ML.NET Model Builder, we can create machine learning models by attempting to import raw data first and over time curate the data, to get better results.
JK will show you how ML.NET works, how to leverage Model Builder, experiment with training data and what to watch out for when building models.
About the speakers
Jernej "JK" Kavka
With 10 years of experience in software engineering across multiple industries like Museums, Government, Banks, gaming, entertainment, Jernej has worked on full stack development of native applications from mobile to desktop applications.
JK loves working on Angular, .NET Core, and cognitive service and his most recent projects have featured Docker and AKS (Azure Kubernetes Services). He now loves containers and sees everything as a container!
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