Mathias Brandewinder on .NET, F#, VSTO and Excel development, and quantitative analysis / machine learning.
by Mathias 6. September 2013 08:15

Recently, Cesar De Souza began moving his .NET machine learning library, Accord.NET, from Google Code to GitHub. The move is still in progress, but that motivated me to take a closer look at the library; given that it is built in C#, with an intended C# usage in mind, I wanted to see how usable it is from F#.

There is a lot in the library; as a starting point, I decided I would try out its Support Vector Machine (SVM), a classic machine learning algorithm, and run it on a classic problem, automatically recognizing hand-written digits. The dataset I will be using here is a subset of the Kaggle Digit Recognizer contest; each example in the dataset is a 28x28 grayscale pixels image, the result of scanning a number written down by a human, and what the actual number is. From that original dataset, I sampled 5,000 examples, which will be used to train the algorithm, and another 500 in a validation set, which we’ll use to evaluate the performance of the model on data it hasn’t “seen before”.

The full example is available as a gist on GitHub.

I’ll be working in a script file within a Library project, as I typically do when exploring data. First, we need to add references to Accord.NET via NuGet:

#r @"..\packages\Accord.\lib\Accord.dll"
#r @"..\packages\Accord.Math.\lib\Accord.Math.dll"
#r @"..\packages\Accord.Statistics.\lib\Accord.Statistics.dll"
#r @"..\packages\Accord.MachineLearning.\lib\Accord.MachineLearning.dll"
open System
open System.IO
open Accord.MachineLearning
open Accord.MachineLearning.VectorMachines
open Accord.MachineLearning.VectorMachines.Learning
open Accord.Statistics.Kernels

Note the added reference to the Accord.dll and Accord.Math.dll assemblies; while the code presented below doesn’t reference it explicitly, it looks like Accord.MachineLearning is trying to load the assembly, which fails miserably if they are not referenced.

Then, we need some data; once the training set and validation set have been downloaded to your local machine (see the gist for the datasets url), that’s fairly easy to do:

let training = @"C:/users/mathias/desktop/dojosample/trainingsample.csv"
let validation = @"C:/users/mathias/desktop/dojosample/validationsample.csv"
let readData filePath =
    File.ReadAllLines filePath
    |> fun lines -> lines.[1..]
    |> (fun line -> line.Split(','))
    |> (fun line -> 
        (line.[0] |> Convert.ToInt32), (line.[1..] |> Convert.ToDouble))
    |> Array.unzip
let labels, observations = readData training

We read every line of the CSV file into an array of strings, drop the headers with array slicing, keeping only items at or after index 1, split each line around commas (so that each line is now an array of strings), retrieve separately the first element of each line (what the number actually is), and all the pixels, which we transform into a float, and finally unzip the result, so that we get an array of integers (the actual numbers), and an array of arrays, the grayscale level of each pixel.


by Mathias 1. September 2013 13:39

I have been back for about a week now, after nearly three weeks on the road, talking about F# all over the US. The first day I woke up in my own bed, my first thought was “where am I again? And where am I speaking tonight?”, now life is slowly getting back to normal, and I thought it would be a good time to share some impressions from the trip.

  • I am very proud to have inaugurated two new F# meetup groups during that trip! The Washington DC F# meetup, organized by @devshorts, is off to a great start, we had a full house at B-Line Medical that evening, with a great crowd mixing F# fans, C# developers, as well as OCaml and Python people, it was great. My favorite moment there was with Sam. Sam, a solid C# developer, looked very worried about writing F# code for the first time. Two hours later, he was so proud (and legitimately so) of having a nice classifier working, all in F#, that he couldn’t resist, and presented his code to the entire group. Nice job! Detroit was my final stop on the road, and didn’t disappoint: the Detroit F# meetup was awesome. It was hosted at the Grand Trunk Pub; while the location had minor logistics drawbacks, it was amply compensated by having food and drinks right there, as well as a great crowd. Thanks to  @OldDutchCap and @JohnBFair for making this happen, this was a suitable grand finale for this trip!
  • In general, August seems to be the blossoming period for F# meetups – two other groups popped up in the same month, one in Minsk, thanks to the efforts of @lu_a_jalla and @sergey_tihon, and one in Paris, spearheaded by @tjaskula, @robertpi and @thinkb4coding, this is very exciting, and I am looking forward to meeting some F#ers next time I stop back home!
  • A lesson I learnt the hard way is that San Francisco is most definitely not a good benchmark for what to wear in August in the US. My first stops were all in the south – Houston, Nashville, Charlotte and Raleigh, and boy was I not ready for the crazy heat and humidity! On the other hand, I can confirm the rumor, the South knows how to make a guest welcome. For that matter, I am extremely grateful to everyone who hosted me during this trip – you know who you are, thank you for all the help.
  • One surprise during this trip was the general level of interest in F#. I regularly hear nonsense sentences like “F# is a niche language”, so I expected smaller crowds in general .NET groups. Well, apparently someone forgot to tell the .NET developers, because I got pretty solid audiences in these groups as well, with an amazing 100 people showing up in Raleigh. Trinug rocked!
  • In general, I was a bit stressed out by running a hands-on machine learning lab with F# novices; for an experienced F# user, it’s not incredibly complex, but for someone who hasn’t used the language before, it’s a bit of a “here is the deep-end of the swimming pool, now go see if you can swim” moment. I was very impressed by how people did in these groups, everyone either finished or ended up very close. Amusingly, in one of the groups, the first person who completed the exercise, in very short time, was… a DBA, who explained that he immediately went for a set-oriented style. Bingo! The lesson for me is that F# is not complicated, but you have to embrace its flow, and largely forget about C#. One trick which seemed to help was to ask the question “how would you write it if you were using only LINQ”. Otherwise, C# developers seemed to often over-think and build code blocks too large for their own good, whereas F# works best by creating very small and simple functions, and then assembling them in larger workflows.
  • Another fun moment was in Boston, where I ran the Machine Learning dojo at Hack/Reduce, language agnostic (thanks @JonnyBoats for making the introductions!). Pretty much every language under the sun was represented (C#, Java, F#, Scala, Python, Matlab, Octave, R, Clojure, Ruby) – but one of the participants still managed to pull “something special”, and tried to implement a classifier entirely in PostgreSQL. It didn’t quite work out, but hats off nevertheless, that was a valiant experiment!
  • As a Frenchman, I take food seriously. As a scientist, I want to see the data. Therefore, I was very excited to have the opportunity to investigate whether Northern Carolina style BBQ is indeed an heresy, first hand. I got the chance to try out BBQ in Houston and Raleigh, and I have to give it to Texas, hands down.


  • Lesson learnt the hard way: do not ever depend on the internet for a presentation. Some of my material was on a Gist on GitHub, and a couple of hours before a presentation, I realized that they were under a DOS attack. Not happy times.
  • I am more and more of a fan of the hands-on, write code in groups format. It has its limitations – you can’t really do it with a very large crowd, and it requires more time than a traditional talk – but it’s a very different experience. One thing I really enjoyed when starting with F# was its interactivity; the “write code and see what happens” experience rekindled the joy of coding for me. The hands-on format captures some of that “happy hacking” spirit, and gets people really engaged. Once someone start writing code, they own it – and working in groups is a great way to accelerate the learning process, and build a community.

Great afternoon with @phillyaltnet crowd hacking at #kaggle machine learning dataset with #fsharpMachine learning and lots of fun with #fsharp @trinug tonight, you guys rocked!

  • I have been complacent with the story “it works on environments other than Windows/Visual Studio”. It does, but the best moment to figure out how to make it work exactly is not during a group coding exercise. In these situations, is your friend – and since I came back, I started actually trying all that out, because “I heard it should work” is just not good enough.
  • I saw probably somewhere between 500 and 1,000 developers during this trip, and while this was completely exhausting, I don’t regret any of it. One of the highpoints of the whole experience was to just get some time to hang out with old or new friends from the F#/functional community – @panesofglass in Houston, @bryan_hunter and the FireFly Logic & @NashFP crew in Nashville, @rickasaurus, @tomaspetricek, @pblasucci, @mitekm and @hmansell in New York City, and @plepilov, @kbattocchi and @talbott in Boston (sorry if I forgot anyone!). If this trip taught me one thing, it’s that there is actually a lot of interest for F# in the .NET community, and beyond – but we, the F# community, are very scattered, and from our smaller local groups, it’s often hard to get a sense for that. Having a chance to talk to all of you guys who have been holding the fort and spreading F# around, discussing what we do, what works and what doesn’t, and simply having a good time, was fantastic. We need more of this – I am incredibly invigorated, and very hopeful that 2014 will be a great year for F#!


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