Built natively in XCode, using Objective-C, C++ and OpenGLES2, Friend Smash for iOS shows you how to integrate the Facebook SDK for iOS to provide easy login, increased engagement and improved organic distribution.

ios-howtos

ios-snapshot-test-case

Snapshot view unit tests for iOS

ios-swagshop

Sample application for iOS 7 demonstrating Open Graph objects, login, profile data, and OG actions.

iterlib

Iterator library.

itorch

IPython kernel for Torch with visualization and plotting

javelin

Large, bloated Javascript framework with an unintuitive, verbose syntax and very few features. Browsing its inelegant, poorly written source is an unwelcome experience.

jcommon

concurrency, collections, stats/analytics, config, testing, etc

jscaml

A compile time transformation from JavaScript to OCaml, along with an OCaml implementation of the JavaScript builtin library.

jsgamebench

Exercise web browsers under game-like conditions

jsgrep

Syntactically-aware grep for JavaScript

jshint

JSHint is a community-driven tool to detect errors in JavaScript code and enforce your team's coding conventions.

jsonpipe

Package jsonpipe provides a io.Reader for Encoding JSON. This is useful to encode JSON without buffering.

jstransform

A simple utility for pluggable JS syntax transforms using the esprima parser.

keyframes

A library for converting Adobe AE shape based animations to a data format and playing it back on Android and iOS devices.

kvocontroller

Simple, modern, thread-safe key-value observing for iOS and OS X.

landingpagedemo

[Archive] A simple landing page made with Parse Hosting

latencytester

Firmware, Schematics, and Mechanicals for the Oculus Latency Tester

learningsimplealgorithms

We present an approach for learning simple algorithms such as copying, multi-digit addition and single digit multiplication directly from examples. Our framework consists of a set of interfaces, accessed by a controller. Typical interfaces are 1-D tapes or 2-D grids that hold the input and output data. For the controller, we explore a range of neural network-based models which vary in their ability to abstract the underlying algorithm from training instances and generalize to test examples with many thousands of digits. The controller is trained using Q-learning with several enhancements and we show that the bottleneck is in the capabilities of the controller rather than in the search incurred by Q-learning.

lex-pass

manipulate a php codebase using haskell to transform the abstract-syntax-tree

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