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    <dc:date>2014-07-15T19:44:51+00:00</dc:date>
    <link>http://electricarchaeology.ca/2014/07/15/doing-ocr-within-r/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[OCR of PDFs within R, if you want text vectors to do something text vectorey with.]]></description>
<dc:subject>ocr osx pdf opensource cli r</dc:subject>
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    <title>knitr: Elegant, flexible and fast dynamic report generation with R | knitr</title>
    <dc:date>2013-04-24T10:26:38+00:00</dc:date>
    <link>http://yihui.name/knitr/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[successor to sweave in that it integrates R an LaTeX, but aims to be a more extensible superset, integrating python, HTML, markdown, restructuredtext...]]></description>
<dc:subject>python restructuredtext r latex</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:26a182b18ac8/</dc:identifier>
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<item rdf:about="http://mc-stan.org/">
    <title>Stan: Project Home</title>
    <dc:date>2012-08-31T04:03:30+00:00</dc:date>
    <link>http://mc-stan.org/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[A Hamiltonian Monte Carlo that translates your models to C++ then compiles them, so that you can do fast hierarchical bayesian inference. Does weird ninja stuff with c++ template functions to automatically differentiate. Now with python support]]></description>
<dc:subject>c++ monte_carlo statistics r bayes python</dc:subject>
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<item rdf:about="http://statisfaction.wordpress.com/2011/12/13/create-maps-with-maptools/">
    <title>Create maps with maptools R package | Statisfaction</title>
    <dc:date>2011-12-14T10:06:45+00:00</dc:date>
    <link>http://statisfaction.wordpress.com/2011/12/13/create-maps-with-maptools/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[How to do stats on the surface of he earth with beautiful visualizations]]></description>
<dc:subject>mapping gis r statistics france</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:0faee4025fba/</dc:identifier>
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<item rdf:about="http://www.shogun-toolbox.org/">
    <title>shogun | A Large Scale Machine Learning Toolbox</title>
    <dc:date>2011-10-21T05:01:32+00:00</dc:date>
    <link>http://www.shogun-toolbox.org/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[
                
                    includes lots of tasty goodies radiating out from the SVM core, such as generalised markovian model learning, HDF5, string kernels, multi-language bindings and an emphasis on scalability.
                
            ]]></description>
<dc:subject>svm learning ai markov r python matlab</dc:subject>
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<item rdf:about="http://www.deducer.org/pmwiki/pmwiki.php?n=Main.DeducerManual">
    <title>Deducer: A GUI for R - Deducer Manual</title>
    <dc:date>2011-10-20T04:52:04+00:00</dc:date>
    <link>http://www.deducer.org/pmwiki/pmwiki.php?n=Main.DeducerManual</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[
                
                    interactive exploratory data munging console for the more intuitive flavour of R user.
                
            ]]></description>
<dc:subject>r gui java</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:8e04d3295060/</dc:identifier>
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<item rdf:about="http://a-little-book-of-r-for-time-series.readthedocs.org/en/latest/">
    <title>Welcome to a Little Book of R for Time Series! — Time Series v0.1 documentation</title>
    <dc:date>2011-09-13T07:38:53+00:00</dc:date>
    <link>http://a-little-book-of-r-for-time-series.readthedocs.org/en/latest/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[A gentle climb up a staircase, atop which is ARIMA.
]]></description>
<dc:subject>R statistics</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:3f3f80b94580/</dc:identifier>
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    <title>A Roadmap for Rich Scientific Data Structures in Python | Quant Pythonista</title>
    <dc:date>2011-09-09T05:18:34+00:00</dc:date>
    <link>http://wesmckinney.com/blog/?p=77</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA["So, this post is a bit of a brain dump on rich data structures in Python and what needs to happen in the very near future. I care about them for statistical computing (I want to build a statistical computing environment that trounces R) and financial data analysis (all evidence leads me to believe that Python is the best all-around tool for the finance space). Other people in the scientific Python community want them for numerous other applications: geophysics, neuroscience, etc. It’s really hard to make everyone happy with a single solution. But the current state of affairs has me rather anxious. And I’d like to explain why..."
]]></description>
<dc:subject>statistics Python R visualisation db nosql has:for</dc:subject>
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<item rdf:about="http://pandas.sourceforge.net/index.html">
    <title>pandas: a python data analysis library — pandas v0.4.0dev documentation</title>
    <dc:date>2011-08-13T11:25:59+00:00</dc:date>
    <link>http://pandas.sourceforge.net/index.html</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA["pandas is a python package providing convenient data structures for time series, cross-sectional, or any other form of “labeled” data, with tools for building statistical and econometric models."

handle data in python intuitively. pass to R for fiddly bits.
]]></description>
<dc:subject>Python R metadata statistics</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:858ee502e4c1/</dc:identifier>
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<item rdf:about="http://www.johndcook.com/blog/2011/06/30/calling-cpp-from-r/">
    <title>Calling C++ from R — The Endeavour</title>
    <dc:date>2011-07-02T00:35:34+00:00</dc:date>
    <link>http://www.johndcook.com/blog/2011/06/30/calling-cpp-from-r/</link>
    <dc:creator>howthebodyworks</dc:creator><dc:subject>vc++ performance R HowTo</dc:subject>
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<item rdf:about="http://www.travisnelson.net/2011/06/09/automating-r-scripts-on-amazon-ec2/">
    <title>Automating R Scripts on Amazon EC2 | Travis Nelson's Blog</title>
    <dc:date>2011-06-26T07:19:27+00:00</dc:date>
    <link>http://www.travisnelson.net/2011/06/09/automating-r-scripts-on-amazon-ec2/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[Overview:

How to setup R on an EC2 instance of Ubuntu 11.04 (Natty Narwhal)
How to setup Apache Tomcat 6.0 web server and configuring it with basic authentication so that we can view our output from R on a password protected webpage
How to automate your R scripts to run as a daily cron job.
]]></description>
<dc:subject>ec2 R amazon HowTo</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:c270e46b7f2a/</dc:identifier>
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<item rdf:about="http://www.drewconway.com/zia/?p=2701">
    <title>EC2 AMI for scientific computing in Python and R « Zero Intelligence Agents</title>
    <dc:date>2011-06-26T07:18:46+00:00</dc:date>
    <link>http://www.drewconway.com/zia/?p=2701</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[Like many people who crunch numbers frequently, I have increasingly been integrating Amazon’s cloud computing services into my daily workflow. In particular, I have been using their elastic cloud computing (EC2) on a regular basis. The service is an excellent way to offload computationally intensive work from your laptop for literally pennies on the dollar.

One drawback that I have found, however, is there are not any obvious pre-configured images, called AMIs, designed for scientific computing in the languages I use most: Python and R. ... Thus began the odyssey of modifying the StarCluster AMI to more fully support scientific computing in Python in R. I have now uploaded and made public the resulting image, which includes several hundred Python and R packages for scientific computing, statistics, machine learning, data mining and visualization.
]]></description>
<dc:subject>Python numpy R ec2 amazon HowTo</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:718a090e9c8b/</dc:identifier>
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<item rdf:about="http://www.cerebralmastication.com/2011/05/shell-scripting-ec2-for-fun-and-profit/">
    <title>Cerebral Mastication » Blog Archive » Shell scripting EC2 for fun and profit</title>
    <dc:date>2011-06-26T07:12:21+00:00</dc:date>
    <link>http://www.cerebralmastication.com/2011/05/shell-scripting-ec2-for-fun-and-profit/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[Lately I’ve been doing some work with creating ad-hoc clusters of EC2 machines. My ultimate goal is to create a simple way to spin up a cluster of EC2 machines for use with Bryan Lewis’s very cool doRedis backend for the R foreach package. But that’s a whole other post. What I was scratching my head about today was that I’d really just like to, with a single command, spin up an EC2 instance, wait for it to come up, and then ssh into it. I do this iteration about 20 times a day when I’m testing things, so it seemed to make sense to shell script it.
To do this, one needs the EC2 command line tools installed on your workstation. In Ubuntu that’s as easy as `sudo apt-get ec2-api-tools`
]]></description>
<dc:subject>ec2 mapreduce R HowTo</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:8addbc348b03/</dc:identifier>
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<item rdf:about="http://exploringdatablog.blogspot.com/2011/04/interestingness-measures.html">
    <title>ExploringDataBlog: Interestingness Measures</title>
    <dc:date>2011-05-30T02:27:14+00:00</dc:date>
    <link>http://exploringdatablog.blogspot.com/2011/04/interestingness-measures.html</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[categorical data has other Shannon-information-like estiamtors of "interestingness"
]]></description>
<dc:subject>statistics r information_theory bubble_economy</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:c4557570196c/</dc:identifier>
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<item rdf:about="http://igraph.sourceforge.net/index.html">
    <title>The igraph library for complex network research</title>
    <dc:date>2011-05-30T02:18:27+00:00</dc:date>
    <link>http://igraph.sourceforge.net/index.html</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[c graph library with r and python support
]]></description>
<dc:subject>networks r python statistics c</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:9224124df217/</dc:identifier>
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<item rdf:about="http://onertipaday.blogspot.com/2008/10/r-upgrade-on-mac-os-x-1055-leopard.html">
    <title>One R Tip A Day: R Upgrade on Mac Os X 10.5.5 (Leopard)</title>
    <dc:date>2011-04-18T04:19:22+00:00</dc:date>
    <link>http://onertipaday.blogspot.com/2008/10/r-upgrade-on-mac-os-x-1055-leopard.html</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[general instructions for upgrading r and keeping your packages magically installed despite its zany clunky library handling.
]]></description>
<dc:subject>r</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:76ffe9735612/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:r"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://connectmv.com/tutorials/r-tutorial/">
    <title>ConnectMV | Process Improvement using Data</title>
    <dc:date>2011-03-09T04:53:01+00:00</dc:date>
    <link>http://connectmv.com/tutorials/r-tutorial/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[interesting bunch of courses on statistical data fiddling
]]></description>
<dc:subject>r howto statistics</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:f65ec9689d96/</dc:identifier>
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	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.burns-stat.com/pages/Tutor/hints_R_begin.html#langs">
    <title>Burns Statistics -- Some Hints for the R Beginner</title>
    <dc:date>2011-01-25T13:08:59+00:00</dc:date>
    <link>http://www.burns-stat.com/pages/Tutor/hints_R_begin.html#langs</link>
    <dc:creator>howthebodyworks</dc:creator><dc:subject>r statistics howto</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:72be37f8b5f8/</dc:identifier>
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	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:howto"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.unidata.ucar.edu/software/netcdf/">
    <title>NetCDF (network Common Data Form)</title>
    <dc:date>2011-01-15T06:07:18+00:00</dc:date>
    <link>http://www.unidata.ucar.edu/software/netcdf/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[storage search and interchange for large array data
]]></description>
<dc:subject>MATLAB ObjC Perl Python R Ruby Tcl Tk c c++ data datamining java</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:de6d2500fca2/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:MATLAB"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:ObjC"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:Perl"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:Python"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:R"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:Ruby"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:Tcl"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:Tk"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:c"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:c++"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:data"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:java"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www2.warwick.ac.uk/fac/sci/moac/students/peter_cock/python/lin_reg/">
    <title>Using Python (and R) to calculate Linear Regressions</title>
    <dc:date>2010-12-03T06:15:58+00:00</dc:date>
    <link>http://www2.warwick.ac.uk/fac/sci/moac/students/peter_cock/python/lin_reg/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[best, simplest example of R<->python interaction i've seen
]]></description>
<dc:subject>r python</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:1458bd678549/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:r"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:python"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://xianblog.wordpress.com/2010/09/13/simply-start-over-and-build-something-better/">
    <title>“simply start over and build something better” « Xi'an's Og</title>
    <dc:date>2010-11-29T05:23:11+00:00</dc:date>
    <link>http://xianblog.wordpress.com/2010/09/13/simply-start-over-and-build-something-better/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[the case for replacing the language of R with somethig else that can access the same statistical power
]]></description>
<dc:subject>r statistics compsci coding</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:0e6f3992be9f/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:r"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:compsci"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:coding"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://tuvalu.santafe.edu/~aaronc/powerlaws/">
    <title>Power-law Distributions</title>
    <dc:date>2010-11-11T02:03:01+00:00</dc:date>
    <link>http://tuvalu.santafe.edu/~aaronc/powerlaws/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[how to find, in a statistically valid fashion, that your data fits a power law.
]]></description>
<dc:subject>statistics scaling powerlaw matlab python r</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:9021519cd0c6/</dc:identifier>
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	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:scaling"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:powerlaw"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:matlab"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:python"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:r"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://strimmerlab.org/software/entropy/">
    <title>R: Entropy and Mutual Information Estimation</title>
    <dc:date>2010-10-25T01:02:23+00:00</dc:date>
    <link>http://strimmerlab.org/software/entropy/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[MI and H estimates
]]></description>
<dc:subject>information_theory r statistics</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:b2b11ec94d19/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:information_theory"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:r"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://rpy.sourceforge.net/rpy2.html">
    <title>http://rpy.sourceforge.net/rpy2.html</title>
    <dc:date>2010-10-19T00:18:24+00:00</dc:date>
    <link>http://rpy.sourceforge.net/rpy2.html</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[the python<->R interface is being rebooted
]]></description>
<dc:subject>r python api statistics</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:ff72f8740594/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:r"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:python"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:api"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://had.co.nz/ggplot2/">
    <title>ggplot. had.co.nz</title>
    <dc:date>2010-10-15T00:08:49+00:00</dc:date>
    <link>http://had.co.nz/ggplot2/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[Tufte-compliant graphing tricks for R
]]></description>
<dc:subject>r visualization statistics academic parsimony</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:0e85e633fb49/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:r"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:visualization"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:academic"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:parsimony"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://zedshaw.com/essays/programmer_stats.html">
    <title>Programmers Need To Learn Statistics Or I Will Kill Them All</title>
    <dc:date>2010-10-01T01:52:37+00:00</dc:date>
    <link>http://zedshaw.com/essays/programmer_stats.html</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[This guy is reliably entertaining. in this case, it's a userful, arrogant rant about what you need to know about stats to push beyond the "mean request time or whatever. highlights:


>The next day we had IBM fixing the problem (turned out to be a single update index command) and we all kept our jobs. That’s what a proper analysis method can do for you.

>still I see software developers begging for gazillions of dollars to buy some crap tool that doesn’t even mention “standard deviation”, but throws “user” around like it’s Dr. Phil treating Robert Downey Jr. for heroin addiction.
]]></description>
<dc:subject>r reference statistics performance compsci dear_me</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:230efc5ec48b/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:r"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:reference"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:performance"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:compsci"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:dear_me"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://csde.washington.edu/statnet/">
    <title>Statnet</title>
    <dc:date>2010-09-21T01:42:39+00:00</dc:date>
    <link>http://csde.washington.edu/statnet/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[network stats for R
]]></description>
<dc:subject>simss phd academic networks r datamining statistics opensource</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:19b4686c8df9/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:simss"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:phd"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:academic"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:networks"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:r"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:opensource"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://rwiki.sciviews.org/doku.php">
    <title>start [R Wiki]</title>
    <dc:date>2010-08-25T02:46:48+00:00</dc:date>
    <link>http://rwiki.sciviews.org/doku.php</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[R can haz wiki
]]></description>
<dc:subject>wiki r howto</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:996082c1f0d6/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:wiki"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:r"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:howto"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://radar.oreilly.com/2010/06/what-is-data-science.html">
    <title>What is data science? - O'Reilly Radar</title>
    <dc:date>2010-06-08T15:17:24+00:00</dc:date>
    <link>http://radar.oreilly.com/2010/06/what-is-data-science.html</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[O'reilly gives an overview of large dataset tools, including some nice machine learning ones
]]></description>
<dc:subject>data mapreduce opensource methodology hps hadoop java r python ai via:datakid schmooze academic phd</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:874de9d2f3ea/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:data"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:mapreduce"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:opensource"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:methodology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:hps"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:hadoop"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:java"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:r"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:python"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:ai"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:via:datakid"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:schmooze"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:academic"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:phd"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://netlogo-r-ext.berlios.de/">
    <title>NetLogo-R-Extension</title>
    <dc:date>2010-03-29T05:35:47+00:00</dc:date>
    <link>http://netlogo-r-ext.berlios.de/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[export from netlogo to R
]]></description>
<dc:subject>r netlogo statistics visualization agents</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:bcaa5f43db21/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:r"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:netlogo"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:visualization"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:agents"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://dist.stat.tamu.edu/pub/rvideos/">
    <title>R Videos</title>
    <dc:date>2010-03-14T18:56:23+00:00</dc:date>
    <link>http://dist.stat.tamu.edu/pub/rvideos/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[learn r monkey-see-monkey-do style
]]></description>
<dc:subject>howto r statistics</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:b79e295710f1/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:howto"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:r"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://ananelson.com/">
    <title>ananelson.com</title>
    <dc:date>2010-02-26T06:54:48+00:00</dc:date>
    <link>http://ananelson.com/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[interesting looking economics simulation person
]]></description>
<dc:subject>schmooze economics simulation visualization r ruby amazon ec2 ireland</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:3fa95aa39280/</dc:identifier>
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	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:economics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:simulation"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:visualization"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:r"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:ruby"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:amazon"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:ec2"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:ireland"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.iq.harvard.edu/blog/netgov/2009/12/goudreau-hunter_tutorial_on_ad.html">
    <title>Complexity and Social Networks Blog: Goudreau-Hunter tutorial on Advanced Social Network Analysis Using R and statnet</title>
    <dc:date>2010-01-03T06:09:17+00:00</dc:date>
    <link>http://www.iq.harvard.edu/blog/netgov/2009/12/goudreau-hunter_tutorial_on_ad.html</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[how to use r plus some graph libraryies to do statistically useful social network analysis.
]]></description>
<dc:subject>r datamining networks statistics</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:85af989dba43/</dc:identifier>
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	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:networks"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://igraph.sourceforge.net/igraphbook/">
    <title>Network Analysis with igraph</title>
    <dc:date>2010-01-03T00:53:08+00:00</dc:date>
    <link>http://igraph.sourceforge.net/igraphbook/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[a noice-looking graph analysis library
]]></description>
<dc:subject>graph networks python r statistics visualization datamining howto</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:3939a4fd53e0/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:graph"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:networks"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:python"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:r"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:visualization"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:howto"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://abeautifulwww.com/2009/10/11/guide-to-getting-started-in-machine-learning/">
    <title>Guide to Getting Started in Machine Learning | A Beautiful WWW</title>
    <dc:date>2009-10-12T23:05:54+00:00</dc:date>
    <link>http://abeautifulwww.com/2009/10/11/guide-to-getting-started-in-machine-learning/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[Instant guid to getting started with machine learning
]]></description>
<dc:subject>learning ai howto phd geek nlp statistics r</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:af8625555b6f/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:ai"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:howto"/>
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