ravnoor

# Here are a few methods for getting text from PDF files. Do read through 
# the instructions carefully! NOte that this code is written for Windows 7,
# slight adjustments may be needed for other OSs

# Tell R what folder contains your 1000s of PDFs
dest <- "G:/somehere/with/many/PDFs"

# make a vector of PDF file names
myfiles <- list.files(path = dest, pattern = "pdf",  full.names = TRUE)

ravnoor

#!/bin/bash 
 
# Default Variable Declarations 
DEFAULT="Default.txt" 
FILEEXT=".ovpn" 
CRT=".crt" 
KEY=".3des.key" 
CA="ca.crt" 
TA="ta.key" 
 

ravnoor

# OSX for Hackers (Mavericks/Yosemite)
#
# Source: https://gist.github.com/brandonb927/3195465

#!/bin/sh

# Some things taken from here
# https://github.com/mathiasbynens/dotfiles/blob/master/.osx

# Ask for the administrator password upfront

ravnoor

#!/bin/bash

# Alot of these configs have been taken from the various places
# on the web, most from here
# https://github.com/mathiasbynens/dotfiles/blob/master/.osx
# and here
# https://gist.github.com/brandonb927/3195465

# Set the colours you can use
black='\033[0;30m'

ravnoor

#!/bin/bash

# Requires: brew install imagemagick --with-little-cms --with-little-cms2

DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
echo ""
echo ""
echo ""
echo ""
echo "All the images in the following folder will be changes: "

ravnoor

#' Get a PubMed search index
#' @param query a PubMed search string
#' @return the XML declaration of the search
#' @example
#' # Which articles discuss the WHO FCTC?
#' pubmed_ask("FCTC OR 'Framework Convention on Tobacco Control'")
pubmed_ask <- function(query) {
  
  # change spaces to + and single-quotes to URL-friendly %22 in query
  query = gsub("'", "%22", gsub(" ", "+", query))

ravnoor

Verify and Repair Disk Permissions via Terminal (Mac OS X)

Verify Permissions

diskutil verifyPermissions /

Repair Permissions

diskutil repairPermissions /

ravnoor

ravnoor

# Implementation of a simple MLP network with one hidden layer. Tested on the iris data set.
# Requires: numpy, sklearn, theano

# NOTE: In order to make the code simple, we rewrite x * W_1 + b_1 = x' * W_1' 
# where x' = [x | 1] and W_1' is the matrix W_1 appended with a new row with elements b_1's. 
# Similarly, for h * W_2 + b_2
import theano
from theano import tensor as T
import numpy as np
from sklearn import datasets

ravnoor

# Example code to demonstrate parallel for loop implementation using joblib
from joblib import Parallel, delayed
import multiprocessing

# Vars
my_list = range(10)
squares = []

# Function to parallelize
def find_square(i):