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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

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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):

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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

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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.

In General

Values

• "Build tools for others that you want to be built for you." - Kenneth Reitz
• "Simplicity is alway better than functionality." - Pieter Hintjens

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1. 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

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Distributed Systems Reading List

Links for Further Reading

• You Can't Sacrifice Partition Tolerance
• Twitter conversation with Jay Kreps about Vector Clocks
• Why Cassandra Doesn't Need Vector Clocks
• Why Vector Clocks are Easy
• Why Vector Clocks are Hard
• Cache is the New RAM
• Neat Algorithms: Paxos

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