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.

    Day 1

    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

    Day 2

    1. Prototype a solution with multiple different ML.NET Model Builder models
    2. Exploring ML.NET SDKs
    3. Automating generation of models with ML.NET CLI
    4. Continuously improving machine learning model and updating applications

    Computer setup

    Recommended to install before the event:

    Jernej Kavka
    Microsoft AI MVP, SSW Solution Architect

    Jernej Kavka (JK) is a Microsoft AI MVP, SSW Solution Architect, and organizer of several user groups like APAC AI and Global AI The Podcast. JK is a full-stack .NET developer, but his passion lies in Azure Cognitive Services, AI and machine learning. He is the main architect behind SSW's virtual receptionist - SophieAI:

    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.

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