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Interactive Computing with F# Jupyter

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Interactive Computing with F# Jupyter
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561
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CC Attribution 2.0 Belgium:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
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Notebooks let you blend code, data, and graphical visualisations to explore and share explanations. I’ll show how you can use F# in Jupyter to investigate data, train machine learning models, and visualise results. You'll learn how to use F# and several NuGet libraries in a more interactive setting than your usual development environment. I'll talk about how we use this in our work on programming biology, and ways other people may find it useful to work with data scientists. It's an open source project https://github.com/fsprojects/IfSharp and there are several ways people could help from connecting to more analysis tools to helping with the migration to .NET Core.