Joseph Dung kod3r

Beyond Web 2.0 - Django and Python in the modern web ecosystem

Django is over 10 years old; but the web that it was built for - the world of "Web 2.0" - doesn't really exist any more. Yes, we still need to rapidly develop database-backed websites, AJAX-enabled, but the modern web is faced with new problems, and new challenges. Many of those challenges involve interacting with devices that aren't desktop machines, and platforms that aren't a traditional browser - places where Python isn't a first-class citizen.

Does this mean we have to abandon Django and Python for other frameworks and languages? Can we keep using Python and Django on the server side and interact with independent client side frameworks? Or can we push Python and Django into these new environments?

In this talk, Dr Russell Keith-Magee will explore the problems, and some potential solutions, to these problems.

Detailed abstract

Source: http://christonard.com/12-free-data-mining-books/

An Introduction to Statistical Learning with Applications in R by James, Witten, Hastie & Tibshirani – This book is fantastic and has helped me quite a bit. It provides an overview of several methods, along with the R code for how to complete them. 426 Pages.
The Elements of Statistical Learning by Hastie, Tibshirani & Friedman – This is an in-depth overview of methods, complete with theory, derivations & code. I’d definitely consider this a graduate level text. I’d also consider it one of the best books available on the topic of data mining. 745 Pages.
A Programmer’s Guide to Data Mining by Ron Zacharski – This one is an online book, each chapter downloadable as a PDF. It’s also still in progress, with chapters being added a few times each year. Probabilistic Programming & Bayesian Methods for Hackers by Cam Davidson-Pilson – This book is absolutely fantastic. The author explains Bayesian statistics, provides several diverse examples of how to a

What

Roll your own iPython Notebook server with Amazon Web Services (EC2) using their Free Tier.

What are we using? What do you need?

An active AWS account. First time sign-ups are eligible for the free tier for a year
One Micro Tier EC2 Instance
With AWS we will use the stock Ubuntu Server AMI and customize it.
Anaconda for Python.
Coffee/Beer/Time

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

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.

Studying for a Tech Interview Sucks, so Here's a Cheat Sheet to Help

This list is meant to be a both a quick guide and reference for further research into these topics. It's basically a summary of that comp sci course you never took or forgot about, so there's no way it can cover everything in depth. It also will be available as a gist on Github for everyone to edit and add to.

Data Structure Basics

###Array ####Definition:

Stores data elements based on an sequential, most commonly 0 based, index.
Based on tuples from set theory.

	import sys
	import colorsys
	from colorz import colorz

	WALLPAPER = '/home/james/.wallpaper'
	COLORS = '/home/james/.colors'
	XRESOURCES = '/home/james/.Xresources'

	cols = ''
	xres = """

	public class PalindromeMaker {
	public String make(String baseString) throws Exception{
	int[] hash= new int[26];
	for(int i=0;i<baseString.length();i++){
	char ch=baseString.charAt(i);
	if(ch<'A' \|\| ch>'Z') throw new Exception("Wrong Input");
	hash[ch-'A']++;
	}
	boolean check=false;
	StringBuilder begin=new StringBuilder();

	#!/usr/bin/python

	import requests, json, pprint, time, socket

	CARBON_SERVER = '0.0.0.0'
	CARBON_PORT = 2003

	def send_msg(message):
	#print 'sending message: %s' % message
	sock = socket.socket()

	Moved to a proprer repositoy, TSWS is a real boy now!

	https://github.com/dfletcher/tsws

	PRs welcomed.