Introduction to Machine Learning with Functional Programming

A session at .NET Fringe 2016

Sunday 10th July, 2016

9:00am to 4:30pm (PST)

Workshop Abstract:

Machine Learning and Functional Programming are both very hot topics these days; they are also both rather intimidating for the beginner. In this workshop, we’ll take a 100% hands-on approach, and learn practical ideas from Machine Learning, by tackling real-world problems and implementing solutions in F#, in a functional style.

In the process, you will see that once you get beyond the jargon, F# and Machine Learning are actually not all that complicated – and fit beautifully together. So if you are curious about what Machine Learning is about, and want to sharpen your developer skills, come with your laptop and… let’s hack together!

What you should expect:

  • no F# or Machine Learning prerequisites: complete beginners are totally welcome,
  • a hands-on introduction to simple Machine Learning ideas you can use, by solving real-world problems,
  • a practical introduction to writing effective F# code,
  • lots of coding on fun problems!

Workshop Schedule:

09:00 Workshop intro: what IS machine learning?
09:30 Lab: automatically recognizing hand-written numbers
11:00 Wrap-up: lessons learnt
11:30 Lab: what language is this text written in?
12:00 Lunch

13:30 Lab (cont'd): what language is this text written in?
14:15 Demo: detecting patterns in data
14:30 Introduction to gradient descent & neural nets
14:45 Lab: recognizing language with a perceptron
15:30 Demo: from perceptrons to deep neural networks
15:45 Demo: scaling machine learning with mbrace.io
16:00 Wrap up & summary.


This will be a hands-on workshop, so be sure to come with a laptop. You’ll also need to install F# with an editor of your choice. To get that, follow the instructions on http://fsharp.org/ for Mac, Windows or Linux. On Mac, we recommend VS Code or Xamarin Studio; on Windows, we recommend VS Code or Visual Studio.

If you’re using Atom or VS Code, follow the installation instructions in "Getting started” on the Ionide page (http://ionide.io/). You'll need to install mono (Mac and Linux) or F# (Windows) and Atom/VS Code itself. Then install the ionide-installer package.

And that’s all, no previous experience with F# or machine learning is needed!

About the speakers

This person is speaking at this event.
Evelina Gabasova

Machine learning, data science, #fsharp and #rstats. bio from Twitter

This person is speaking at this event.
Mathias Brandewinder

Figuring out things, one model at a time.

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Time 9:00am4:30pm PST

Date Sun 10th July 2016



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