ilovejs

/*
    BrowserDetect.browser == 'Explorer';
    BrowserDetect.version <= 8;
*/
var BrowserDetect =
{
    init: function () {
        this.browser = this.searchString(this.dataBrowser) || "Other";
        this.version = this.searchVersion(navigator.userAgent) || this.searchVersion(navigator.appVersion) || "Unknown";
    },

ilovejs

library(shiny)
library(ggplot2)
library(RCurl)
library(reshape2)

ilovejs

(loop [i 0]
  (if (< i 10)
    (recur (inc 1))
    i))

(str "2 is " (if (even? 2) "even" "odd"))

(if (true? false) "impossible!")
 
(defn factorial [x]

ilovejs

//remove lein
rm -r ~/.m2
echo $PATH 
ls /usr/bin | grep lein
...
rm -r /usr/bin/lein

//install lein
wget https://raw.github.com/technomancy/leiningen/stable/bin/lein
sudo mv lein /usr/bin/lein

ilovejs

$ sudo apt-get remove mplayer

$ sudo apt-get --purge remove lighttpd

//To list all installed package
dpkg --list
dpkg --list | less
dpkg --list | grep -i 'http'

ilovejs

#!/usr/bin/env ruby

# Please read http://otobrglez.opalab.com for more information about this code.

class Book < Struct.new(:title)

  def words
    @words ||= self.title.gsub(/[a-zA-Z]{3,}/).map(&:downcase).uniq.sort
  end

ilovejs

# This method finds related articles using Jaccard index (optimized for PostgreSQL).
# More info: http://en.wikipedia.org/wiki/Jaccard_index

class Article < ActiveRecord::Base

  def related(limit=10)
    Article.find_by_sql(%Q{
      SELECT
      	a.*,
      	( SELECT array_agg(t.name) FROM taggings tg, tags t

ilovejs

Method 1:

download node-xxx.gz on http://nodejs.org/

//extract file
tar -xf node-xxx.gz


(ps: compression can be done):
tar -cf node.gz folder1 folder2

ilovejs

Movie Recommendations with k-Nearest Neighbors and Cosine Similarity

---

Introduction

The k-nearest neighbors (k-NN) algorithm is among the simplest algorithms in the data mining field. Distances / similarities are calculated between each element in the data set using some distance / similarity metric ^^[1]^ that the researcher chooses (there are many distance / similarity metrics), where the distance / similarity between any two elements is calculated based on the two elements' attributes. A data element’s k-NN are the k closest data elements according to this distance / similarity.

---

1. A distance metric measures distance; the higher the distance the further apart the neighbors. A similarity metric measures similarity; the higher the similarity the closer the neighbors.

ilovejs

http://installrails.com/steps/choose_os