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The Best of the Best Practices (BOBP) Guide for Python

A "Best of the Best Practices" (BOBP) guide to developing in Python.

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

	sudo apt-get -y update
	sudo apt-get -y upgrade
	sudo apt-get -y dist-upgrade
	sudo apt-get -y install git make python-dev python-setuptools libblas-dev gfortran g++ python-pip python-numpy python-scipy liblapack-dev
	sudo pip install ipython nose
	sudo apt-get install screen
	sudo pip install --upgrade git+git://github.com/Theano/Theano.git
	wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1204/x86_64/cuda-repo-ubuntu1204_5.5-0_amd64.deb
	sudo dpkg -i cuda-repo-ubuntu1204_5.5-0_amd64.deb
	sudo apt-get update

	import theano
	from pylearn2.models import mlp
	from pylearn2.training_algorithms import sgd
	from pylearn2.termination_criteria import EpochCounter
	from pylearn2.datasets.dense_design_matrix import DenseDesignMatrix
	import numpy as np
	from random import randint


	class XOR(DenseDesignMatrix):

	import theano
	from pylearn2.models import mlp
	from pylearn2.train_extensions import best_params
	from pylearn2.training_algorithms import sgd, learning_rule
	from pylearn2.utils import serial
	from pylearn2.termination_criteria import MonitorBased
	from pylearn2.datasets.dense_design_matrix import DenseDesignMatrix
	from sklearn.preprocessing import StandardScaler
	import numpy as np
	from random import randint