mathias-brandewinder

let square (x:float) = x * x

square 10.0

// fsharp.formatting // fsharp project scaffold

// 1. promote script to unit test // 2. promote script to documentation // 3. discard :)

mathias-brandewinder

Material

https://onedrive.live.com/redir?resid=2BCBE7155876A728!1097143&authkey=!ABrD4JQvAPqfUKE&ithint=folder%2czip

mathias-brandewinder

Rules

Round 1: 45 minutes.

• Smallest total score wins
• Shortest solution for each problem gets 0 points, others score the difference from the best
• 5 points bonus for each working tweeted solution on @fsibot

Show & Tell

Round 2: 30 minutes

mathias-brandewinder

1) editor

VSCode + Ionide
Bonus: Ionide Paket for package management

http://ionide.io/
https://fsprojects.github.io/Paket/

2) presentations

mathias-brandewinder

type Observation = {
    SearchTerms: string
    ProductTitle: string 
    }
    with member this.SearchLength = this.SearchTerms.Length |> float

type Relevance = float

type Predictor = Observation -> Relevance

mathias-brandewinder

open System.IO

type Image = int []
type Observation = { Label:int; Pixels:Image }
type Model = Image -> int

let euclDistance (img1:Image) (img2:Image) =
    (img1,img2) ||> Seq.map2 (fun x y -> (x-y) * (x-y)) |> Seq.sum

let train trainingSet = 

mathias-brandewinder

let source = __SOURCE_DIRECTORY__

#load "NaiveBayes.fs"
open MachineLearning.NaiveBayes

open System
open System.IO
open System.Text
open System.Text.RegularExpressions

mathias-brandewinder

#r @"..\packages\R.NET.1.5.5\lib\net40\RDotNet.dll"
#r @"..\packages\RDotNet.FSharp.0.1.2.1\lib\net40\RDotNet.FSharp.dll"
#r @"..\packages\R.NET.1.5.5\lib\net40\RDotNet.NativeLibrary.dll"
#r @"..\packages\RProvider.1.0.2\lib\RProvider.dll"

open System
open RDotNet
open RProvider

open RProvider.``base``

mathias-brandewinder

Quickstart: Creating Charts


One of the compelling features of R is its ability to create beautiful charts.
With the R Type Provider, you can use all of R capabilities from F#, and create simple charts quickly to explore and visualize your data on-the-fly, as well as generate publication quality graphics that can be exported to virtually any format.


Charts Basics

Basic charts can be found in the graphics package. Assuming you installed the R Type Provider in your project from NuGet, you can reference the required libraries and packages this way:

mathias-brandewinder

This dojo is directly inspired by the Digit Recognizer competition from Kaggle.com:
http://www.kaggle.com/c/digit-recognizer
The datasets below are simply shorter versions of the training dataset from Kaggle.


The dataset
*************

2 datasets can be downloaded here: