fivejjs

#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
#  pegasos.py
#  
#  Copyright 2013 nipun batra <nipunb@iiitd.ac.in>
#  
#  This program is free software; you can redistribute it and/or modify
#  it under the terms of the GNU General Public License as published by
#  the Free Software Foundation; either version 2 of the License, or

fivejjs

import os
import sys
from getpass import getpass

import gdata.docs.service
import gdata.spreadsheet.service


'''
    get user information from the command line argument and 

fivejjs

#!/bin/bash
# GTK+ and Firefox for Amazon Linux
# Written by Joseph Lawson 2012-06-03
# http://joekiller.com
# http://joekiller.com/2012/06/03/install-firefox-on-amazon-linux-x86_64-compiling-gtk/

# chmod 755 ./gtk-firefox.sh
# sudo ./gtk-firefox.sh

fivejjs

from TwitterSearch import *
import csv

def get_tweets(query, max = 2000):
    # takes a search term (query) and a max number of tweets to find
    # gets content from twitter and writes it to a csv bearing the name of your query
    
    i = 0
    search = query

fivejjs

### author: Jinjun Sun 
### email: jsunster@gmail.com
### refer to https://gist.github.com/linkerlin/4654376#file-classpathhacker-py-L20
### refer to http://www.jython.org/jythonbook/en/1.0/appendixB.html#working-with-classpath

import java.sql as sql
import java.lang as lang


class classPathHacker :

fivejjs

#! /usr/bin/python
# Dispatch - synchronize two folders

import os
import filecmp
import shutil
from stat import *

class Dispatch:
    ''' This class represents a synchronization object '''

fivejjs

1. General Background and Overview

• Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
• Models and Issues in Data Stream Systems
• Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
• Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
• [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep

fivejjs

import numpy as np
import pymc
import pdb

def unconditionalProbability(Ptrans):
   """Compute the unconditional probability for the states of a
   Markov chain."""

   m = Ptrans.shape[0]

fivejjs

""" Theano CRBM implementation.

For details, see:
http://www.uoguelph.ca/~gwtaylor/publications/nips2006mhmublv
Sample data:
http://www.uoguelph.ca/~gwtaylor/publications/nips2006mhmublv/motion.mat

@author Graham Taylor"""

import numpy

fivejjs

Expand The Edinburgh Twitter FSD Corpus

The Python scripts attached here take care of the following tedious work, and should help one quickly get started with some real work on the corpus:

• Respect the Twitter API rate limits and throttle API hits.
• Don't hit the API for already expanded tweet ID's, so you can resume tweet expansion after stopping midway.
• Parse the API response and dump it into the correct column in the sqlite3 database.
• Gracefully handle exceptions while acquiring tweets from the API.
• Wrap version 1.1 of the Twitter API.
• Start from a specified tweet ID, assuming the input file is sorted in increasing order of tweet ID.