wrunk

#!/usr/bin/env/python
# 
# More of a reference of using jinaj2 without actual template files.
# This is great for a simple output transformation to standard out.
#
# Of course you will need to "sudo pip install jinja2" first!
#
# I like to refer to the following to remember how to use jinja2 :)
# http://jinja.pocoo.org/docs/templates/
#

MohamedAlaa

tmux shortcuts & cheatsheet

start new:

tmux

start new with session name:

tmux new -s myname

dergachev

OS X Screencast to animated GIF

This gist shows how to create a GIF screencast using only free OS X tools: QuickTime, ffmpeg, and gifsicle.

Instructions

To capture the video (filesize: 19MB), using the free "QuickTime Player" application:

jfreels

d3js: Dynamic Scatter plot based on Select input.

rxaviers

People

:bowtie:	😄 :smile:	😆 :laughing:
😊 :blush:	😃 :smiley:	☺️ :relaxed:
😏 :smirk:	😍 :heart_eyes:	😘 :kissing_heart:
😚 :kissing_closed_eyes:	😳 :flushed:	😌 :relieved:
😆 :satisfied:	😁 :grin:	😉 :wink:
😜 :stuck_out_tongue_winking_eye:	😝 :stuck_out_tongue_closed_eyes:	😀 :grinning:
😗 :kissing:	😙 :kissing_smiling_eyes:	😛 :stuck_out_tongue:

dobsondev

# ~/.bash_profile

[[ -s ~/.bashrc ]] && source ~/.bashrc

export CLICOLOR=1
export LSCOLORS=GxFxCxDxBxegedabagaced

alias subl='/Applications/Sublime\ Text\ 2.app/Contents/SharedSupport/bin/subl'
alias ls='ls -GFh'
alias ll='ls -l'

wch

Type: Shiny
Title: actionButton demo
License: MIT
Author: Winston Chang <winston@rstudio.com>
AuthorUrl: http://www.rstudio.com/
Tags: actionbutton
DisplayMode: Showcase

neubig

#!/usr/bin/env python
# -*- coding: utf-8 -*-

# This is a simplified implementation of the LSTM language model (by Graham Neubig)
#
#  LSTM Neural Networks for Language Modeling
#  Martin Sundermeyer, Ralf Schlüter, Hermann Ney
#  InterSpeech 2012
# 
# The structure of the model is extremely simple. At every time step we

Nemitek

import pandas as pd  
from random import random

flow = (list(range(1,10,1)) + list(range(10,1,-1)))*1000  
pdata = pd.DataFrame({"a":flow, "b":flow})  
pdata.b = pdata.b.shift(9)  
data = pdata.iloc[10:] * random()  # some noise  

import numpy as np

AustinRochford

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [