Sardor Muminov muminoff

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[Abstraction without overhead: traits in Rust] (http://blog.rust-lang.org/2015/05/11/traits.html)

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

	import tensorflow as tf
	import skimage.transform
	from skimage.io import imsave, imread
	import os
	from os import listdir, path
	from os.path import isfile, join

	def get_directory(folder):
	foundfile = []

	import tensorflow as tf
	import skimage.transform
	from skimage.io import imsave, imread

	def load_image(path):
	img = imread(path)
	# crop image from center
	short_edge = min(img.shape[:2])
	yy = int((img.shape[0] - short_edge) / 2)
	xx = int((img.shape[1] - short_edge) / 2)

	var express = require('express');
	var redis = require('redis');

	const serverType = process.argv[2];
	const serverHost = process.argv[3];
	const serverPort = parseInt(process.argv[4]);

	const redisPort = 6379;
	const redisHost = '127.0.0.1';

	http://www.depesz.com/2011/12/02/the-secret-ingredient-in-the-webscale-sauce/
	http://www.craigkerstiens.com/2012/11/30/sharding-your-database/
	https://github.com/markokr/pghashlib

	http://www.niwi.be/2013/03/06/table-partitioning-with-postgresql/
	https://blog.engineyard.com/2013/scaling-postgresql-performance-table-partitioning
	http://instagram-engineering.tumblr.com/post/10853187575/sharding-ids-at-instagram
	http://instagram-engineering.tumblr.com/post/40781627982/handling-growth-with-postgres-5-tips-from-instagram
	http://media.postgresql.org/sfpug/instagram_sfpug.pdf

	#!/usr/bin/env python
	# -- coding: utf-8 --

	"""

	pip install networkx distance pattern

	In Flipboard's article[1], they kindly divulge their interpretation
	of the summarization technique called LexRank[2].

	<html>
	<head>
	<title>D3 Axis Example</title>
	<script src="http://d3js.org/d3.v2.js"></script>
	</head>

	<body>
	<button id="rescale" onclick="rescale();">Rescale</button>
	<script>
	var width = 700,