July: Machine Learning simplified for Developers+Time Travel With SQL Server

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July .NET User Group - Double Header! Machine Learning simplified for Developers with ML.NET + Time Travel With SQL Server

Session #1: Machine Learning simplified for Developers with ML.NET - presented by Jernej "Jk" Kavka

Do you want to try machine learning, but don't want to invest too much time learning a new programming language or some other complicated API?

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 presenter
With around 10 years of experience in software engineering, Jernej has worked on full-stack .NET development, mobile applications, and Microsoft Cognitive Services. He worked for some of Australia's largest corporations, with great customer satisfaction.

Session #2: Time Travel With SQL Server– presented by Joel Gallagher

Available in Azure SQL & SQL Server 2016, Temporal Tables allow us to travel back in time, querying the database at any given moment.
This also gives us features as auditing, telemetry and insights, all with very minimal setup & maintenance required.

Wont' be a dry SQL talk! Fun datasets & narratives to spell out the features & uses that Temporal Tables gives us.

About the presenter
Joel Gallagher has been writing software professionally for around 20 years, both in Australia and abroad. He is currently working as an Analytics Developer for StarRez in Melbourne, playing with SQL, PowerBI and Azure in equal measures.

He's interested in Database technologies, Cloud operations, Analytics & Insights, and Data Visualization. He is a MCSA (SQL Server) and is currently working on his Masters of Applied Statistics.