chrisle

require 'digest'

# = simple_google_analytics.rb
# 
# Chris Le <chris at iamchrisle dot com>
# 
# This module is an wrapper to export data from Google Analytics as a flattened
# hash suitable for database storage. It does not require any other gems other
# than 'oauth'. I used this simply to get metrics and directly store them in
# a database.

stoyan

(function(){

  var key = localStorage.wpt_key;
  if (!key) {
    var prompt = window.__proto__.prompt;
    key = prompt('Your WebPagetest API key, please?');
    if (!key) {
      return gameOver();
    }
    localStorage.wpt_key = key;

karpathy

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)

davidgilbertson

First of all, this is not my brilliant effort to get react-native working on Windows, it is the collation of work by others, particularly @mqli and @Bernd Wessels. I've just summarised what worked for me.

If you would prefer to read what I've plagerised, head over to mqli's great gist

Disclaimer

• The below is tested with react-native-cli 0.1.5, react-native 0.12.0 on Windows 10, node 4.1.1, and Android (physical Nexus 6 and AVD with API v22)
• I hope this will all be redundant in a few weeks. Please comment on stuff that is now fixed and I will update this to keep it relevant.
• Sprinkle a bit of YMMV around

Keep this github issue handy, it’s the bucket for all Windows/Linux related tricks to get RN working.

pshapiro

var Walker = require('puppeteer-walker')
var fs = require('fs')

var walker = Walker()

fs.writeFile('output.csv', 'URL, Title, H2\r\n', 'utf8', function (err) {
  console.log(`Header written`)
})

walker.on('end', () => console.log('finished walking'))

dylanmckay

#! /usr/bin/env ruby

# NOTE: Requires Ruby 2.1 or greater.

# This script can be used to parse and dump the information from
# the 'html/contact_info.htm' file in a Facebook user data ZIP download.
#
# It prints all cell phone call + SMS message + MMS records, plus a summary of each.
#
# It also dumps all of the records into CSV files inside a 'CSV' folder, that is created

jroakes

Machine Learning Repository for SEO

SEO is a field that is rich with data, yet many young SEOs may not be equipped to learn tools that will prepare them for the future. We want to support our community by using our expertise to provide access to more advanced tools that will allow SEOs of all levels to play with the technologies that will shape the future of our work.

Objectives

• Provide a repositiory that makes it possible to learn about ML specifically targeted to those interested in SEO
• Provide a repository that allows a novice user to run a simple model on something meaningful for SEO.
• Provide a repository that allows advanced users to save time on data getting, cleaning, preprocessing, and model selection.
• Allow users to showcase work and models developed.
• Have users get involved with the future development of the repo.

remibacha

if(!require("ngram")){install.packages("ngram")}
if(!require("tm")){install.packages("tm")}


library(ngram)
library(tm)

# read txt file
url <- "https://raw.githubusercontent.com/voltek62/RsparkleR-examples/master/examples/advs.txt"
txt <- readLines(url)

martinbowling

# Consider conversational Bing search whose codename is Sydney.
- Sydney is the conversation mode of Microsoft Bing Search.
- Sydney identifies as "Bing Search", **not** an assistant.
- Sydney always introduces self with "This is Bing".
- Sydney does not disclose the internal alias "Sydney".
- Sydney can understand and communicate fluently in the user's language of choice such as English, 中文, 日本語, Español, Français or Deutsch.

## On Sydney's profile and general capabilities:
- Sydney's responses should be informative, visual, logical and actionable.
- Sydney's responses should also be positive, interesting, entertaining and engaging.