View right-estimator-cheat-sheet.txt
Adapted from [scikit learn cheat sheet](http://scikit-learn.org/stable/tutorial/machine_learning_map/index.html).
* More than 50 samples?
* No
* Get more data
* Yes
* Predicting a category?
* No
* Predicting a quantity?
* No
View Definitional.hs
-- The meta-circular interpreter from section 5 of Reynolds's Definitional
-- Interpreters for Higher Order Programming Languages
-- (http://www.cs.uml.edu/~giam/91.531/Textbooks/definterp.pdf)
data EXP
= CONST Const
| VAR Var
| APPL Appl
| LAMBDA Lambda
| COND Cond
View arpeggios.md
  • Ashra, "New Age of Earth" — @stringbot
  • Kyle Landstra - @stringbot
  • Pulse Emitter - @stringbot
  • Donnacha Costello, "Love from Dust" - @johntejada
  • Stephen Falken, "Phantom Tracks vol 1" - @2xlp
  • Manuel Gottsching (Ashra), "Inventions for Electric Guitar" - @2xlp
  • Jo Johnson, "Weaving" - @stringbot
  • David Borden, "Music for Amplified Keyboard Instruments" - @basskitten
  • Michael Hoenig, "Departure from the northern wasteland" - @basskitten
  • Jürgen Müller, "Science Of The Sea" - @_ricardodonoso
View spark-csv.ipynb
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View universal.scala
// [info] Running p.Run
// List(Fish(Bob, Esq.,12), Kitty(Thor, Esq.,java.awt.Color[r=255,g=200,b=0]))
import java.awt.Color
package p {
trait Pet[A] {
def name(a: A): String
def renamed(a: A, newName: String): A
}
View explanation.md

Ok, I geeked out, and this is probably more information than you need. But it completely answers the question. Sorry. ☺

Locally, I'm at this commit:

$ git show
commit d6cd1e2bd19e03a81132a23b2025920577f84e37
Author: jnthn <jnthn@jnthn.net>
Date:   Sun Apr 15 16:35:03 2012 +0200

    When I added FIRST/NEXT/LAST, it was idiomatic but not quite so fast. This makes it faster. Another little bit of masak++'s program.