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<rdf:RDF xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" xmlns="http://purl.org/rss/1.0/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"><channel rdf:about="https://www.bibsonomy.org/user/tmalsburg/tutorial"><title>BibSonomy bookmarks for /user/tmalsburg/tutorial</title><link>https://www.bibsonomy.org/user/tmalsburg/tutorial</link><description>BibSonomy RSS Feed for /user/tmalsburg/tutorial</description><items><rdf:Seq><rdf:li rdf:resource="http://www.rensenieuwenhuis.nl/r-project/r-sessions-index/"/><rdf:li rdf:resource="http://zoonek2.free.fr/UNIX/48_R/06.html"/><rdf:li rdf:resource="http://aidanjm.wordpress.com/2007/02/15/split-lossless-audio-ape-flac-wv-wav-by-cue-file/"/><rdf:li rdf:resource="http://clojure.blip.tv/"/><rdf:li rdf:resource="http://www.tufts.edu/~gdallal/LHSP.HTM"/><rdf:li rdf:resource="http://doc.ddart.net/shell/awk/"/><rdf:li rdf:resource="http://www.brains-minds-media.org/archive/222"/><rdf:li rdf:resource="http://www.physics.csbsju.edu/stats/KS-test.html"/><rdf:li rdf:resource="http://cocosci.berkeley.edu/tom/bayes.html"/><rdf:li rdf:resource="http://www.qcad.org/qcad/manual_reference/"/><rdf:li rdf:resource="http://eagain.net/articles/git-for-computer-scientists/"/><rdf:li rdf:resource="http://www.gigamonkeys.com/book/macros-defining-your-own.html"/><rdf:li rdf:resource="http://java.sun.com/developer/JDCTechTips/2002/tt0219.html"/><rdf:li rdf:resource="http://jmcpherson.org/editing.html"/><rdf:li rdf:resource="http://cns-alumni.bu.edu/~slehar/fourier/fourier.html"/><rdf:li rdf:resource="http://schemecookbook.org/"/><rdf:li rdf:resource="http://www.onlamp.com/pub/a/onlamp/2005/11/17/r_for_statistics.html?page=1"/><rdf:li rdf:resource="http://www.cs.ubc.ca/~murphyk/Bayes/bnintro.html"/><rdf:li rdf:resource="http://home.comcast.net/~prunesquallor/macro.txt"/><rdf:li rdf:resource="http://www.trapexit.org/"/></rdf:Seq></items></channel><item rdf:about="http://www.rensenieuwenhuis.nl/r-project/r-sessions-index/"><title>R-Sessions Index | Curving Normality</title><description></description><link>http://www.rensenieuwenhuis.nl/r-project/r-sessions-index/</link><dc:creator>tmalsburg</dc:creator><dc:date>2010-05-18T08:14:39+02:00</dc:date><dc:subject>documentation gnur index resource statistics tutorial </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2010-05-18T08:14:39+02:00&#034; href=&#034;http://www.rensenieuwenhuis.nl/r-project/r-sessions-index/&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://www.rensenieuwenhuis.nl/r-project/r-sessions-index/&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/documentation"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/gnur"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/index"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/resource"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/statistics"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tutorial"/></rdf:Bag></taxo:topics></item><item rdf:about="http://zoonek2.free.fr/UNIX/48_R/06.html"><title>Clustering in GNU-R</title><description></description><link>http://zoonek2.free.fr/UNIX/48_R/06.html</link><dc:creator>tmalsburg</dc:creator><dc:date>2009-02-12T13:19:20+01:00</dc:date><dc:subject>clustering gnu-r statistics tutorial </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2009-02-12T13:19:20+01:00&#034; href=&#034;http://zoonek2.free.fr/UNIX/48_R/06.html&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://zoonek2.free.fr/UNIX/48_R/06.html&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/clustering"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/gnu-r"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/statistics"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tutorial"/></rdf:Bag></taxo:topics></item><item rdf:about="http://aidanjm.wordpress.com/2007/02/15/split-lossless-audio-ape-flac-wv-wav-by-cue-file/"><title>Split lossless audio (ape, flac, wv, wav) by cue file in Ubuntu « aidanjm’s stuff</title><description>Tutorial on processing of CUE files etc.</description><link>http://aidanjm.wordpress.com/2007/02/15/split-lossless-audio-ape-flac-wv-wav-by-cue-file/</link><dc:creator>tmalsburg</dc:creator><dc:date>2008-12-21T12:58:59+01:00</dc:date><dc:subject>audio tipstricks tool tutorial unix </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;Tutorial on processing of CUE files etc.&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/audio"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tipstricks"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tool"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tutorial"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/unix"/></rdf:Bag></taxo:topics></item><item rdf:about="http://clojure.blip.tv/"><title>Clojure on blip.tv</title><description></description><link>http://clojure.blip.tv/</link><dc:creator>tmalsburg</dc:creator><dc:date>2008-11-06T12:28:14+01:00</dc:date><dc:subject>clojure introduction programming tutorial video </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2008-11-06T12:28:14+01:00&#034; href=&#034;http://clojure.blip.tv/&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://clojure.blip.tv/&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/clojure"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/introduction"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/programming"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tutorial"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/video"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www.tufts.edu/~gdallal/LHSP.HTM"><title>The Little Handbook of Statistical Practice</title><description>Concise and insightful as far as I can see.</description><link>http://www.tufts.edu/~gdallal/LHSP.HTM</link><dc:creator>tmalsburg</dc:creator><dc:date>2008-06-15T16:00:38+02:00</dc:date><dc:subject>handbook statistics tutorial </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;Concise and insightful as far as I can see.&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/handbook"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/statistics"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tutorial"/></rdf:Bag></taxo:topics></item><item rdf:about="http://doc.ddart.net/shell/awk/"><title>Getting Started with awk</title><description></description><link>http://doc.ddart.net/shell/awk/</link><dc:creator>tmalsburg</dc:creator><dc:date>2008-05-13T21:23:25+02:00</dc:date><dc:subject>programming tipstricks tutorial </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2008-05-13T21:23:25+02:00&#034; href=&#034;http://doc.ddart.net/shell/awk/&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://doc.ddart.net/shell/awk/&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/programming"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tipstricks"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tutorial"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www.brains-minds-media.org/archive/222"><title>Realistic Single Cell Modeling – from Experiment to Simulation — Brains, Minds &amp; Media</title><description></description><link>http://www.brains-minds-media.org/archive/222</link><dc:creator>tmalsburg</dc:creator><dc:date>2007-11-12T16:30:05+01:00</dc:date><dc:subject>computationalneuroscience modeling neuron simulation tutorial </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2007-11-12T16:30:05+01:00&#034; href=&#034;http://www.brains-minds-media.org/archive/222&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://www.brains-minds-media.org/archive/222&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/computationalneuroscience"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/modeling"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/neuron"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/simulation"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tutorial"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www.physics.csbsju.edu/stats/KS-test.html"><title>Kolmogorov-Smirnov Test</title><description>The Kolmogorov-Smirnov test (KS-test) tries to determine if two datasets differ significantly. The KS-test has the advantage of making no assumption about the distribution of data. (Technically speaking it is non-parametric and distribution free.) Note however, that this generality comes at some cost: other tests (for example Student&#039;s t-test) may be more sensitive if the data meet the requirements of the test. In addition to calculating the D statistic, this page will report if the data seem normal or lognormal. (If it is silent, assume normal data at your own risk!) It will enable you to view the data graphically which can help you understand how the data is distributed.</description><link>http://www.physics.csbsju.edu/stats/KS-test.html</link><dc:creator>tmalsburg</dc:creator><dc:date>2007-09-28T16:09:40+02:00</dc:date><dc:subject>introduction statistics tutorial </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;The Kolmogorov-Smirnov test (KS-test) tries to determine if two datasets differ significantly. The KS-test has the advantage of making no assumption about the distribution of data. (Technically speaking it is non-parametric and distribution free.) Note however, that this generality comes at some cost: other tests (for example Student&amp;#039;s t-test) may be more sensitive if the data meet the requirements of the test. In addition to calculating the D statistic, this page will report if the data seem normal or lognormal. (If it is silent, assume normal data at your own risk!) It will enable you to view the data graphically which can help you understand how the data is distributed.&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/introduction"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/statistics"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tutorial"/></rdf:Bag></taxo:topics></item><item rdf:about="http://cocosci.berkeley.edu/tom/bayes.html"><title>Computational Cognitive Science lab: Reading list on Bayesian methods</title><description>Tom Griffith:  This list is intended to introduce some of the tools of Bayesian statistics and machine learning that can be useful to computational research in cognitive science. The first section mentions several useful general references, and the others provide supplementary readings on specific topics. If you would like to suggest some additions to the list, contact Tom Griffiths.</description><link>http://cocosci.berkeley.edu/tom/bayes.html</link><dc:creator>tmalsburg</dc:creator><dc:date>2007-07-30T22:26:21+02:00</dc:date><dc:subject>bayesian bayesiannetworks bibliography library tutorial </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;Tom Griffith:  This list is intended to introduce some of the tools of Bayesian statistics and machine learning that can be useful to computational research in cognitive science. The first section mentions several useful general references, and the others provide supplementary readings on specific topics. If you would like to suggest some additions to the list, contact Tom Griffiths.&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/bayesian"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/bayesiannetworks"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/bibliography"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/library"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tutorial"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www.qcad.org/qcad/manual_reference/"><title>QCad User Reference Manual</title><description></description><link>http://www.qcad.org/qcad/manual_reference/</link><dc:creator>tmalsburg</dc:creator><dc:date>2007-07-27T19:51:03+02:00</dc:date><dc:subject>cad construction manual reference software tutorial </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2007-07-27T19:51:03+02:00&#034; href=&#034;http://www.qcad.org/qcad/manual_reference/&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://www.qcad.org/qcad/manual_reference/&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/cad"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/construction"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/manual"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/reference"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/software"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tutorial"/></rdf:Bag></taxo:topics></item><item rdf:about="http://eagain.net/articles/git-for-computer-scientists/"><title>Tv&#039;s cobweb: Git for Computer Scientists</title><description></description><link>http://eagain.net/articles/git-for-computer-scientists/</link><dc:creator>tmalsburg</dc:creator><dc:date>2007-07-19T11:49:45+02:00</dc:date><dc:subject>contentmanagement git sourcecontrolmanagement tutorial </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2007-07-19T11:49:45+02:00&#034; href=&#034;http://eagain.net/articles/git-for-computer-scientists/&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://eagain.net/articles/git-for-computer-scientists/&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/contentmanagement"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/git"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/sourcecontrolmanagement"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tutorial"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www.gigamonkeys.com/book/macros-defining-your-own.html"><title>Macros: Defining Your Own</title><description></description><link>http://www.gigamonkeys.com/book/macros-defining-your-own.html</link><dc:creator>tmalsburg</dc:creator><dc:date>2007-06-10T11:18:09+02:00</dc:date><dc:subject>lisp macros metaprogramming tutorial </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2007-06-10T11:18:09+02:00&#034; href=&#034;http://www.gigamonkeys.com/book/macros-defining-your-own.html&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://www.gigamonkeys.com/book/macros-defining-your-own.html&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/lisp"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/macros"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/metaprogramming"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tutorial"/></rdf:Bag></taxo:topics></item><item rdf:about="http://java.sun.com/developer/JDCTechTips/2002/tt0219.html"><title>JDC Tech Tips: February 19, 2002</title><description>small JMF tutorial</description><link>http://java.sun.com/developer/JDCTechTips/2002/tt0219.html</link><dc:creator>tmalsburg</dc:creator><dc:date>2007-04-25T15:14:36+02:00</dc:date><dc:subject>java multimedia programming tutorial </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;small JMF tutorial&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/java"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/multimedia"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/programming"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tutorial"/></rdf:Bag></taxo:topics></item><item rdf:about="http://jmcpherson.org/editing.html"><title>Efficient Editing With vim - Jonathan McPherson</title><description>To me, vi is Zen.
To use vi is to practice zen.
Every command is a koan.
Profound to the user,
unintelligible to the uninitiated.
You discover truth every time you use it.</description><link>http://jmcpherson.org/editing.html</link><dc:creator>tmalsburg</dc:creator><dc:date>2007-01-06T14:05:32+01:00</dc:date><dc:subject>tutorial tools vi unix editor </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;To me, vi is Zen.
To use vi is to practice zen.
Every command is a koan.
Profound to the user,
unintelligible to the uninitiated.
You discover truth every time you use it.&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tutorial"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tools"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/vi"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/unix"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/editor"/></rdf:Bag></taxo:topics></item><item rdf:about="http://cns-alumni.bu.edu/~slehar/fourier/fourier.html"><title>An Intuitive Explanation of Fourier Theory</title><description>Fourier theory is pretty complicated mathematically. But there are some beautifully simple holistic concepts behind Fourier theory which are relatively easy to explain intuitively. There are other sites on the web that can give you the mathematical formulation of the Fourier transform. I will present only the basic intuitive insights here, as applied to spatial imagery.</description><link>http://cns-alumni.bu.edu/~slehar/fourier/fourier.html</link><dc:creator>tmalsburg</dc:creator><dc:date>2006-12-04T22:56:40+01:00</dc:date><dc:subject>mathematics tutorial </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;Fourier theory is pretty complicated mathematically. But there are some beautifully simple holistic concepts behind Fourier theory which are relatively easy to explain intuitively. There are other sites on the web that can give you the mathematical formulation of the Fourier transform. I will present only the basic intuitive insights here, as applied to spatial imagery.&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/mathematics"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tutorial"/></rdf:Bag></taxo:topics></item><item rdf:about="http://schemecookbook.org/"><title>Scheme Cookbook</title><description>With many many recipes.</description><link>http://schemecookbook.org/</link><dc:creator>tmalsburg</dc:creator><dc:date>2006-11-11T17:41:44+01:00</dc:date><dc:subject>tipstricks tutorial lisp documentation programming scheme </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;With many many recipes.&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tipstricks"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tutorial"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/lisp"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/documentation"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/programming"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/scheme"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www.onlamp.com/pub/a/onlamp/2005/11/17/r_for_statistics.html?page=1"><title>Analyzing Statistics with GNU R</title><description></description><link>http://www.onlamp.com/pub/a/onlamp/2005/11/17/r_for_statistics.html?page=1</link><dc:creator>tmalsburg</dc:creator><dc:date>2006-11-06T10:47:40+01:00</dc:date><dc:subject>tutorial statistics </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2006-11-06T10:47:40+01:00&#034; href=&#034;http://www.onlamp.com/pub/a/onlamp/2005/11/17/r_for_statistics.html?page=1&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://www.onlamp.com/pub/a/onlamp/2005/11/17/r_for_statistics.html?page=1&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tutorial"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/statistics"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www.cs.ubc.ca/~murphyk/Bayes/bnintro.html"><title>A Brief Introduction to Graphical Models and Bayesian Networks</title><description></description><link>http://www.cs.ubc.ca/~murphyk/Bayes/bnintro.html</link><dc:creator>tmalsburg</dc:creator><dc:date>2006-10-25T11:03:21+02:00</dc:date><dc:subject>bayes inference modeling networks reasoning tutorial </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2006-10-25T11:03:21+02:00&#034; href=&#034;http://www.cs.ubc.ca/~murphyk/Bayes/bnintro.html&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://www.cs.ubc.ca/~murphyk/Bayes/bnintro.html&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/bayes"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/inference"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/modeling"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/networks"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/reasoning"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tutorial"/></rdf:Bag></taxo:topics></item><item rdf:about="http://home.comcast.net/~prunesquallor/macro.txt"><title>JRM&#039;s Syntax-rules Primer for the Merely Eccentric</title><description>In learning to write Scheme macros, I have noticed that it is easy to find both trivial examples and extraordinarily complex examples, but there seem to be no intermediate ones. I have discovered a few tricks in writing macros and perhaps some people will find them helpful.</description><link>http://home.comcast.net/~prunesquallor/macro.txt</link><dc:creator>tmalsburg</dc:creator><dc:date>2006-09-21T11:27:58+02:00</dc:date><dc:subject>functionalprogramming tutorial lisp programming scheme macros </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;In learning to write Scheme macros, I have noticed that it is easy to find both trivial examples and extraordinarily complex examples, but there seem to be no intermediate ones. I have discovered a few tricks in writing macros and perhaps some people will find them helpful.&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/functionalprogramming"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tutorial"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/lisp"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/programming"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/scheme"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/macros"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www.trapexit.org/"><title>trapexit</title><description>The purpose is to create the one-stop place where to find Erlang information.  At trapexit you will find: Software that is not in the standard OTP distribution, Documentation and HOWTOs, The Erlang discussion forum, Links to other Erlang sites</description><link>http://www.trapexit.org/</link><dc:creator>tmalsburg</dc:creator><dc:date>2006-08-23T16:23:15+02:00</dc:date><dc:subject>samplecode tutorial documentation erlang programming </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;The purpose is to create the one-stop place where to find Erlang information.  At trapexit you will find: Software that is not in the standard OTP distribution, Documentation and HOWTOs, The Erlang discussion forum, Links to other Erlang sites&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/samplecode"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tutorial"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/documentation"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/erlang"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/programming"/></rdf:Bag></taxo:topics></item></rdf:RDF>