Getting Started with Machine Learning using ML.NET
Want to get started with machine learning but don't know where to start? Have you got an Excel spreadsheet, SQL Database or CSV lying around and wondering if you can use it to experiment with Machine Learning? In this workshop, we'll start from a CSV exported by a service, and go all the way to an application that uses Machine Learning to make clever decisions. We will cover: 1. What does a developer need to know about Machine Learning? 2. How does ML.NET help getting started with ML? 3. Quickly prototype a solution with ML.NET Model Builder 4. Improve solution with simple data science rules 5. Integrate a machine learning solution into your application 6. Continuously improving machine learning model and updating applications
Jernej Kavka (JK) is an SSW Senior Software Architect, Microsoft AI MVP and organizer of the Brisbane AI user group. JK is a full-stack .NET developer, but his passion lies in cogitative services, AI and machine learning. He is the main architect behind SSW's virtual receptionist - SophieAI: https://sswsophie.com
He is also very active in the developer community and enjoys speaking at conferences like NDC, DDD, as well as User Groups and Hack Days.