Mathias Brandewinder
Mathias Brandewinder has been writing software in C# for about 10 years, and loving every minute of it, except maybe for a few release days. He is an F# MVP, the author of "Machine Learning Projects for .NET Developers" (Apress), enjoys arguing about code and how to make it better, and gets very excited when discussing TDD or F#.
His other professional interests are applied math and probability. If you want to know more about him, you can check out his blog at or find him on Twitter as @brandewinder.
Talks I've Given
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Dungeons, Dragons and Functions
Featuring Mathias Brandewinder
Dungeons & Dragons, or D&D, is the grand-daddy of all role-playing games. While playing D&D is great fun, the rules are a bit daunting for the beginner. The basic rulebook, the PHB, clocks in at a solid 300 pages, and can be extended with multiple additional rule sets. This should...
domain-modeling gaming f# functional-programming -
Keynote: Deep Learning with CNTK and F#
Featuring Mathias Brandewinder
Deep Learning is a powerful and mysterious sounding Machine Learning technique. It is based on neural networks, and has shown impressive results in areas as different as computer vision, speech recognition, or automated language translation. And, with the recent release of the Microsoft Cognitive...
functional-programming fsharp fsharpx -
Agile experiments in Machine Learning with F#
Featuring Mathias Brandewinder
Just like traditional applications development, machine learning involves writing code. One aspect where the two differ is the workflow. While software development follows a fairly linear process (design, develop, and deploy a feature), machine learning is a different beast. You work on a single...
microservices -
Here Be Dragons: Mapping the F# World
Featuring Mathias Brandewinder
Join Mathias Brandewinder in this Opening Keynote for #ProgFSharpLDN 2016!
fsharp progfsharp progfsharpldn dragons mapping keynote -
Making good predictions from many bad ones
Featuring Mathias Brandewinder
Making bad predictions is pretty easy. But what if you could find a way to take many simple and mediocre prediction models, and combine them into a meta-model that works better than the sum of its individual parts? This question is the focus of what Machine Learning people call Ensemble Methods....
progfsharp progfsharpldn fsharp machine-learning ml ensemble-methods -
Building a Twitter bot with F#
Featuring Mathias Brandewinder
In this talk, I'll explain how I built that bot from the ground up, and present some of the techniques I used, which might be applicable more broadly:
f# azure twitter-bot -
Treasures, Traps and F#
Featuring Mathias Brandewinder
In this hands-on workshop, we will drop an innocent and brainless creature in a world of traps and treasures, and write code to give it a brain and help it automatically learn winning strategies.
fsharp .net machine-learning -
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Building an App!
Featuring Scott Wlaschin, Rachel Reese and Mathias Brandewinder
In the final session of the beginners track, you will be a complete app. There will be a choice of what you can build to suit your particular interest!
f# .net functional-programming -
Ham Or Spam - Hands on Machine Learning with Mathias Brandewinder
Featuring Mathias Brandewinder
In this session, we'll learn about the Naive Bayes classifier, and take a classic Machine Learning problem, recognizing Spam from Ham.
f# machine-learning functional-programming -
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Pac-Man Kata
Featuring Phil Trelford and Mathias Brandewinder
Join Phil Trelford and Mathias Brandewinder for this fun session on Pac-Man-Kata at #progfsharp!
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Machine Learning with F#
Featuring Phil Trelford and Mathias Brandewinder
Join Phil Telford and Mathias Brandewinder for this hands on session. In this tutorial Phil and Mathias will introduce practical Machine Learning techniques.