Prof. Dr. Shishir Urdhwareshe shishironline

Readable Bookmarklet

Bookmarklet Browser Enhancement Readability

Readable is an application that helps you read more of the web. It reformats text — on any website — according to your exact specifications.

#How I built an audio book reader for my nearly blind grandfather

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Last year, when visiting my family back home in Holland, I also stopped by my grand-parents. My grand-father, now 93 years old, had always been a very active man. However, during the presceding couple of months, he'd gone almost completely blind and now spent his days sitting in a chair. Trying to think of something for him to do, I suggested he try out audio books. After finally convincing him -- he said audio books were for sad old people -- that listening to a well performed recording is actually a wonderful experience, I realized the problem of this idea.

####The problem with audio devices and the newly blind. After my first impulse to jump up and go buy him an

Clojure Destructuring Tutorial and Cheat Sheet

(Related blog post)

Simply put, destructuring in Clojure is a way extract values from a datastructure and bind them to symbols, without having to explicitly traverse the datstructure. It allows for elegant and concise Clojure code.

Vectors and Sequences

The introduction to Reactive Programming you've been missing

(by @andrestaltz)

This tutorial as a series of videos

If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.

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=rep1&t

	#!/usr/bin/perl

	use strict;
	use warnings FATAL => 'all';

	use Storable ();
	use Math::BigInt ();
	use JSON ();
	use Path::Class ();
	use Net::Twitter ();

	param([String]$OutputFolder=$null,[String]$ExtensionId=$null,[Switch]$Remove, [Switch]$WhatIf)

	##: Globals
	$retval = $false

	##: If OutputFolder param wasn't given, output the audit file to the desktop
	if(!$OutputFolder -or !(Test-Path -Path $OutputFolder)) {
	$auditfolderpath = "$($env:USERPROFILE)\Desktop"
	} else {
	$auditfolderpath = $OutputFolder

	koans:
	image: clojure
	command: lein koan run
	volumes:
	- ./clojure-koans:/clojure-koans
	working_dir: /clojure-koans

	repl:
	image: clojure
	command: lein repl

	var externalObj = {key: 'value'};

	var items = {
	obj: {
	'string prop': 'string val',
	5: 10,
	nested: [[3, [5, 2]]],
	'function': function(){return true;},
	reference: externalObj
	},

	" A minimal vimrc for new vim users to start with.
	"
	" Referenced here: http://vimuniversity.com/samples/your-first-vimrc-should-be-nearly-empty
	"
	" Original Author: Bram Moolenaar <Bram@vim.org>
	" Made more minimal by: Ben Orenstein
	" Modified by : Ben McCormick
	" Last change: 2014 June 8
	"
	" To use it, copy it to