Session Details

Machine learning on .NET: F# FTW  

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9:15 AM Sunday
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Machine Learning and Data Science are red-hot topics right now. Practitioners routinely use a wide range of tools, from Python to R or Hadoop, and yet, C# is conspicuously absent from that arsenal. Does this mean .NET is not suitable for this domain? In this talk, I'll explain why I think it can be, as long as you use the right language for the job, namely F#. F# is a functional first language, with a concise and expressive syntax that will feel familiar to data scientists used to Python or Matlab. It combines the performance and maintenability benefits of statically typed languages, with the flexibility of Type Providers, a unique mechanism that enables the seamless consumption of virtually any datasources. And as a first-class .NET citizen, it interops smoothly with C#. So if you are interested in a language that can handle both flexible data exploration, and the pressure of a real production system, come check out what F# has to offer!

The Speakers


Mathias Brandewinder

I have been writing software on .NET for 10 years, mostly C#, until I fell in love with F# and functional programming. I enjoy arguing about code and how to make it better, and get very excited when discussing testing or F#. My other professional interests are applied math and machine learning. If you want to know more about me, you can check out my blog here or find me on Twitter as @brandewinder.
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