marcelcaraciolo

#-*- coding: utf-8 -*-

import re
import nltk
from nltk.tokenize import RegexpTokenizer
from nltk import bigrams, trigrams
import math


stopwords = nltk.corpus.stopwords.words('portuguese')

fnielsen

# $Id: Nielsen2012Python_case.py,v 1.2 2012/09/02 16:55:25 fn Exp $

# Define a url as a Python string (note we are only getting 100 documents)
url = "http://wikilit.referata.com/" + \
    "wiki/Special:Ask/" + \
    "-5B-5BCategory:Publications-5D-5D/" + \
    "-3FHas-20author%3DAuthor(s)/-3FYear/" + \
    "-3FPublished-20in/-3FAbstract/-3FHas-20topic%3DTopic(s)/" + \
    "-3FHas-20domain%3DDomain(s)/" +  \
    "format%3D-20csv/limit%3D-20100/offset%3D0"

iandanforth

#############################################################################
# Full Imports

from __future__ import division
import math
import random

"""
This is a pure Python implementation of the K-means Clustering algorithmn. The
original can be found here:

bistaumanga

'''Implementation and of K Means Clustering
Requires : python 2.7.x, Numpy 1.7.1+'''
import numpy as np

def kMeans(X, K, maxIters = 10, plot_progress = None):

    centroids = X[np.random.choice(np.arange(len(X)), K), :]
    for i in range(maxIters):
        # Cluster Assignment step
        C = np.array([np.argmin([np.dot(x_i-y_k, x_i-y_k) for y_k in centroids]) for x_i in X])

abonander

package org.logician.sorta

import scala.util.Random
import scala.math
import scala.collection.mutable
import scala.collection.mutable.ArrayBuffer

/**
 * Created with IntelliJ IDEA.
 * User: Austin

songron

Codes for Machine Learning Foundations(NTU)
台湾国立大学《机器学习基石》（Coursera版）相关的代码、编程作业等。

课程地址：https://class.coursera.org/ntumlone-001/

vladimirtsyupko

git fetch --all
git reset --hard origin/master
git pull origin master

bsweger

Useful Pandas Snippets

A personal diary of DataFrame munging over the years.

Data Types and Conversion

Convert Series datatype to numeric (will error if column has non-numeric values)
(h/t @makmanalp)

LeCoupa

#!/bin/bash
#####################################################
# Name: Bash CheatSheet for Mac OSX
# 
# A little overlook of the Bash basics
#
# Usage:
#
# Author: J. Le Coupanec
# Date: 2014/11/04

aweijnitz

#!/bin/bash

sudo apt-get -y install cups
sudo apt-get -y install cups-pdf

# add pdf printer to cups 
#   - named files end up in ~/PDF/
#   - unnamed files are stored in /var/spool/cups-pdf/ANONYMOUS/, such as PDF:s created by streaming bytes over an API 
sudo lpadmin -p cups-pdf -v cups-pdf:/ -E -P /usr/share/ppd/cups-pdf/CUPS-PDF.ppd