kastnerkyle

# Author: Kyle Kastner
# License: BSD 3-Clause
# For a reference on parallel processing in Python see tutorial by David Beazley
# http://www.slideshare.net/dabeaz/an-introduction-to-python-concurrency
# Loosely based on IBM example
# http://www.ibm.com/developerworks/aix/library/au-threadingpython/
# If you want to download all the PASCAL VOC data, use the following in bash...
"""
#! /bin/bash
# 2008
wget http://host.robots.ox.ac.uk/pascal/VOC/voc2008/VOCtrainval_14-Jul-2008.tar
# 2009
wget http://host.robots.ox.ac.uk/pascal/VOC/voc2009/VOCtrainval_11-May-2009.tar
# 2010
wget http://host.robots.ox.ac.uk/pascal/VOC/voc2010/VOCtrainval_03-May-2010.tar
# 2011
wget http://host.robots.ox.ac.uk/pascal/VOC/voc2011/VOCtrainval_25-May-2011.tar
# 2012
wget http://host.robots.ox.ac.uk/pascal/VOC/voc2012/VOCtrainval_11-May-2012.tar
# Latest devkit
wget http://host.robots.ox.ac.uk/pascal/VOC/voc2012/VOCdevkit_18-May-2011.tar
"""
try:
    import Queue
except ImportError:
    import queue as Queue
import threading
import ti

kukuruza

from math import sqrt

def put_kernels_on_grid (kernel, pad = 1):

  '''Visualize conv. filters as an image (mostly for the 1st layer).
  Arranges filters into a grid, with some paddings between adjacent filters.

  Args:
    kernel:            tensor of shape [Y, X, NumChannels, NumKernels]
    pad:               number of black pixels around each filter (between them)

shagunsodhani

The Batch Normalization paper describes a method to address the various issues related to training of Deep Neural Networks. It makes normalization a part of the architecture itself and reports significant improvements in terms of the number of iterations required to train the network.

Issues With Training Deep Neural Networks

Internal Covariate shift

Covariate shift refers to the change in the input distribution to a learning system. In the case of deep networks, the input to each layer is affected by parameters in all the input layers. So even small changes to the network get amplified down the network. This leads to change in the input distribution to internal layers of the deep network and is known as internal covariate shift.

It is well established that networks converge faster if the inputs have been whitened (ie zero mean, unit variances) and are uncorrelated and internal covariate shift leads to just the opposite.

ebenolson

FROM ubuntu:trusty

########################################
#
# openslide 3.4.1 image based on Ubuntu:trusty
#
#######################################

# Set Locale

hnykda

import pandas as pd  
from random import random

flow = (list(range(1,10,1)) + list(range(10,1,-1)))*100
pdata = pd.DataFrame({"a":flow, "b":flow})  
pdata.b = pdata.b.shift(9)  
data = pdata.iloc[10:] * random()  # some noise  

import numpy as np

calderonroberto

#!/bin/python

# Dependencies:
# pip install flask
# pip install redis

from flask import Flask
from flask import request
import flask
import redis

jasonleonhard

javascript: (function () {
  // the css we are going to inject
  var css =
      "html {" +
      "    -webkit-filter: invert(100%);" +
      "    -moz-filter:    invert(100%);" +
      "    -o-filter:      invert(100%);" +
      "    -ms-filter:     invert(100%);" +
      "}",
    head = document.getElementsByTagName("head")[0],

Prithvirajbilla

// With little creativity and some coding skills you can do a lot of things using this code to annoy some one.
// works on the first chat box opened. only works in google chrome!
function dispatch(target) {
   var evt = document.createEvent("Event"); 
   evt.initEvent("keydown",true,true);
   evt.keyCode = 13;
   evt.which = 13;
   target.dispatchEvent(evt);
}

Prithvirajbilla

//Works on http://web.whatsapp.com
// With little creativity and some coding skills you can do a lot of things using this code to annoy some one.
function dispatch(target, eventType, char) {
   var evt = document.createEvent("TextEvent");    
   evt.initTextEvent (eventType, true, true, window, char, 0, "en-US");
   target.focus();
   target.dispatchEvent(evt);
}
function triggerClick() {
  var event = new MouseEvent('click', {

staringispolite

Puts on glasses:

(•_•)
( •_•)>⌐■-■
(⌐■_■)

Takes off glasses ("mother of god..."):

(⌐■_■)
( •_•)>⌐■-■