bwhite

"""Information Retrieval metrics

Useful Resources:
http://www.cs.utexas.edu/~mooney/ir-course/slides/Evaluation.ppt
http://www.nii.ac.jp/TechReports/05-014E.pdf
http://www.stanford.edu/class/cs276/handouts/EvaluationNew-handout-6-per.pdf
http://hal.archives-ouvertes.fr/docs/00/72/67/60/PDF/07-busa-fekete.pdf
Learning to Rank for Information Retrieval (Tie-Yan Liu)
"""
import numpy as np

staltz

The introduction to Reactive Programming you've been missing

(by @andrestaltz)

---

This tutorial as a series of videos

If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.

---

jpsim

//
//  JAZMusician.h
//  JazzyApp
//

#import <Foundation/Foundation.h>

/**
 JAZMusician models, you guessed it... Jazz Musicians!
 From Ellington to Marsalis, this class has you covered.

Avaq

const I  = x => x
const K  = x => y => x
const A  = f => x => f (x)
const T  = x => f => f (x)
const W  = f => x => f (x) (x)
const C  = f => y => x => f (x) (y)
const B  = f => g => x => f (g (x))
const S  = f => g => x => f (x) (g (x))
const S_ = f => g => x => f (g (x)) (x)
const S2 = f => g => h => x => f (g (x)) (h (x))

olih

Processing JSON using jq

jq is useful to slice, filter, map and transform structured json data.

Installing jq

On Mac OS

brew install jq

andymatuschak

A composable pattern for pure state machines with effects

State machines are everywhere in interactive systems, but they're rarely defined clearly and explicitly. Given some big blob of code including implicit state machines, which transitions are possible and under what conditions? What effects take place on what transitions?

There are existing design patterns for state machines, but all the patterns I've seen complect side effects with the structure of the state machine itself. Instances of these patterns are difficult to test without mocking, and they end up with more dependencies. Worse, the classic patterns compose poorly: hierarchical state machines are typically not straightforward extensions. The functional programming world has solutions, but they don't transpose neatly enough to be broadly usable in mainstream languages.

Here I present a composable pattern for pure state machiness with effects,

blainerothrock

#!/usr/bin/env xcrun swift -O

/*
gen.swift is a direct port of cfdrake's helloevolve.py from Python 2.7 to Swift 3
-------------------- https://gist.github.com/cfdrake/973505 ---------------------
gen.swift implements a genetic algorithm that starts with a base
population of randomly generated strings, iterates over a certain number of
generations while implementing 'natural selection', and prints out the most fit
string.
The parameters of the simulation can be changed by modifying one of the many

b1naryth1ef

Pillow

(64, 64)
        0.217446804047 total time
        217446.804047 ns / op
(128, 128)
        0.085732460022 total time
 85732.460022 ns / op

yossorion

What I Wish I'd Known About Equity Before Joining A Unicorn

Disclaimer: This piece is written anonymously. The names of a few particular companies are mentioned, but as common examples only.

This is a short write-up on things that I wish I'd known and considered before joining a private company (aka startup, aka unicorn in some cases). I'm not trying to make the case that you should never join a private company, but the power imbalance between founder and employee is extreme, and that potential candidates would

hwayne

EXTENDS Integers, TLC, Sequences
CONSTANTS Devices

(* --algorithm BatchInstall
variables
  AppScope \in [Devices -> {0, 1}];
  Installs \in [Devices -> BOOLEAN];
  batch_pool = {};
  lock = FALSE;