<! --------------------------------------------------------------------------->
<li> Jan. 13: Flavors of languages (Mahabal, Stalzer)
<ul>
<li> <a href="http://www.astro.caltech.edu/~george/aybi199/Lec2_Mahabal.pdf"> Ashish's slides (pdf) </a>
<ul>
<li> Pages on programming languages:
<ul>
<li> <a href="http://en.wikipedia.org/wiki/Comparison_of_programming_languages"> Wikipedia article on comparing programming languages </a>
<li> <a href="http://www.engin.umd.umich.edu/CIS/course.des/cis400/"> UMich CIS 400 course </a>
<li> <a href="http://microsoft.toddverbeek.com/lang.html"> Microsoft's wisdom </a>
</ul>
<li> <a href="http://www.math.chalmers.se/~rjmh/Papers/whyfp.pdf"> J. Hughes: "Why functional programming matters" </a>
<li> <a href="http://www.csse.monash.edu.au/~lloyd/tildeFP/Lambda/"> L. Allison's pages on Lambda calculus </a>
<li> <a href="http://www.perl.org/tpc/1998/Perl_Language_and_Modules/Efficient%20Perl/handout.html"> J. Macdonald on Efficiency and Perl </a>
<li> <a href="http://perl.plover.com/Stream/stream.htm"> Hamming's numbers in Perl </a> *
<a href="http://lml.ls.fi.upm.es/~jjmoreno/hamming.pr"> and in Prolog </a>
<li> <a href="http://shootout.alioth.debian.org"> Computer language benchmarks game </a>
<li> Geek humor:
<ul>
<li> <a href="http://www-users.cs.york.ac.uk/~susan/joke/foot.htm"> How to shoot yourself in the foot </a>
<li> <a href="http://www.aegisub.net/2008/12/if-programming-languages-were-religions.html"> If languages were religions </a>
<li> <a href="http://99-bottles-of-beer.net/"> 99 bottles of beer </a>
</ul>
</ul>
<li> <a href="http://www.astro.caltech.edu/~george/aybi199/Lec2_Stalzer.pdf"> Mark's slides (pdf) </a>
<ul>
<li> <a href="http://en.wikipedia.org/wiki/Programming_language_theory"> Wikipedia article on Programming Language Theory </a>
<li> <a href="http://www.ibm.com/developerworks/power/library/pa-cellperf/"> IBM Cell Broadband Engine Architecture </a>
<li> <a href="http://top500.org"> op 500 list of world's fastest computers </a>
<li> <a href="http://java.sun.com/products/hotspot/whitepaper.html"> The Java HotSpot Performance Engine Architecture </a>
<li> <a href="http://techresearch.intel.com/articles/Tera-Scale/1514.htm"> Ct: C for Throughput Computing </a>
</ul>
</ul><p>
<! --------------------------------------------------------------------------->
<li> Jan. 15, 20, 22: Intro to Python for scientific applications (Aivazis)
<ul>
<li> <a href="http://www.astro.caltech.edu/~george/aybi199/Lec3_Aivazis.pdf"> Michael's slides (pdf) </a>
<li> <a href="http://www.python.org"> www.python.org </a>
<li> <a href="http://docs.python.org"> docs.python.org </a>
</ul><p>
<! --------------------------------------------------------------------------->
<li> Jan. 27, 29, Feb. 3: Databases (Graham)
<ul>
<li> <a href="http://www.astro.caltech.edu/~george/aybi199/Lec6_Graham.pdf"> Matthew's slides, part I (pdf) </a>
<li> <a href="http://www.astro.caltech.edu/~george/aybi199/Lec7_Graham.pdf"> Matthew's slides, part II (pdf) </a>
<li> <a href="http://www.astro.caltech.edu/~george/aybi199/Lec8_Graham.pdf"> Matthew's slides, part III (pdf) </a>
</ul><p>
<! --------------------------------------------------------------------------->
<li> Feb. 5, 10, 12: Scientific visualization (Lombeyda)
<ul>
<li> <a href="http://www.astro.caltech.edu/~george/aybi199/Lec9_Lombeyda.pdf"> Santiago's slides, part I (pdf) </a>
<li> <a href="http://www.astro.caltech.edu/~george/aybi199/Lec10_Lombeyda.pdf"> Santiago's slides, part II (pdf) </a>
<li> <a href="http://www.astro.caltech.edu/~george/aybi199/Lec11_Lombeyda.pdf"> Santiago's slides, part III (pdf) </a>
<li> Some visualization packages:
<ul>
<li> <a href="http://www.r-project.org/"> R-project </a>
<li> <a href="http://www.rforge.net/Rserve"> Rserve </a>
<li> <a href="http://rosuda.org/mondrian/"> Mondrian </a>
<li> <a href="http://www.molegro.com/mdm-product.php"> Molegro </a>
<li> <a href="http://davis.wpi.edu/~xmdv/"> XMDV </a>
<li> <a href="http://www.tableausoftware.com/products/trial"> Tableau </a>
<li> <a href="http://www.star.bris.ac.uk/~mbt/topcat/"> Topcat </a>
</ul>
</ul><p>
<! --------------------------------------------------------------------------->
<li> Feb. 17: Introduction to data mining (Djorgovski)
<ul>
<li> <a href="http://www.astro.caltech.edu/~george/aybi199/Lec12_Djorgovski.pdf"> George's slides (pdf) </a>
<li> <a href="http://www.astro.caltech.edu/~george/aybi199/Lec12_Borne.pdf"> Kirk Borne's slides shown by George (pdf) </a>
<li> Some useful links:
<ul>
<li> <a href="http://www.kdnuggets.com/"> Gregory Piatetsky-Shapiro's KDNuggets (LOTS of good links) </a>
<li> <a href="http://www.the-data-mine.com/"> Andy Pryke's The Data Mine </a>
<li> <a href="http://www.kdd.org/"> ACM's Special Interest Group on Knowledge Discovery in Databases </a>
<li> <a href="http://www.sigkdd.org/explorations/issue.php?issue=current"> ... and their newsletter, "Explorations" </a>
<li> <a href="http://www.autonlab.org/tutorials/"> Andrew Moore's statistics and data mining tutorials </a>
<li> <a href="http://thames.cs.rhul.ac.uk/~fionn/classification-society/"> The Classification Society of North America (CSNA) </a>
<li> <a href="http://www.cs.waikato.ac.nz/~ml/weka/"> Weka package and links </a>
<li> <a href="http://www.csse.monash.edu.au/~dld/mixture.modelling.page.html"> David Dowe's mixture modeling links </a>
<li> <a href="http://astro.u-strasbg.fr/~fmurtagh/mda-sw/"> Fionn Murtagh's multivariate data analysis software and links </a>
<li> <a href="http://lib.stat.cmu.edu/"> StatLib at CMU </a>
<li> <a href="http://astrostatistics.psu.edu/statcodes/"> StatCodes at PSU </a>
<li> <a href="http://homepages.inf.ed.ac.uk/rbf/IAPR/"> IAPR Pattern Recognition Education Resources </a>
<li> <a href="http://www.astrostatistics.psu.edu/vostat/"> VOStat @ PSU </a>
<li> <a href="http://vostat.caltech.edu/"> VOStat @ Caltech </a>
<li> <a href="http://www.samsi.info/workshops/prevsamsiworkshops.shtml"> SAMSI Workshops and Tutorials </a>
</ul>
</ul><p>
<! --------------------------------------------------------------------------->
<li> Feb. 19: Unsupervised classifiers (Donalek, Graham)
<ul>
<li> <a href="http://www.astro.caltech.edu/~george/aybi199/Lec13_Donalek.pdf"> Ciro's slides (pdf) </a>
<li> <a href="http://www.astro.caltech.edu/~george/aybi199/Lec13_Graham.pdf"> Matthew's slides (pdf) </a>
</ul><p>
<! --------------------------------------------------------------------------->
<li> Feb. 24: Supervised classifiers (Donalek)
<ul>
<li> <a href="http://www.astro.caltech.edu/~george/aybi199/Lec14_Donalek.pdf"> Ciro's slides (pdf) </a>
<ul>
<li> <a href="http://leenissen.dk/fann/"> FANN (Fast Artificial Neural Networks) </a>
<li> <a href="http://www.ncrg.aston.ac.uk/netlab/index.php"> Netlab Toolbox (Matlab) </a>
<li> <a href="http://www.cis.hut.fi/projects/somtoolbox/"> SOM Toolbox (Matlab) </a>
<li> <a href="http://www.csie.ntu.edu.tw/~cjlin/libsvm/"> SVM library LIBSVM </a>
<li> <a href="http://voneural.na.infn.it/"> VONeural/DAME project </a>
</ul>
<li> A few links about Decision Trees:
<ul>
<li> <a href="http://en.wikipedia.org/wiki/Decision_Trees"> Wikipedia article (general) </a>
<li> <a href="http://en.wikipedia.org/wiki/Decision_tree_learning"> Wikipedia article (DT learning) </a>
<li> <a href="http://adsabs.harvard.edu/abs/1995AJ....109.2401W"> An application in astronomy: star-galaxy classification for the DPOSS survey </a>
</ul>
</ul><p>
<! --------------------------------------------------------------------------->
<li> Feb. 26: Introduction to Bayesian methods (Mahabal)
<ul>
<li> <a href="http://www.astro.caltech.edu/~george/aybi199/Lec15_Mahabal.pdf"> Ashish's slides (pdf) </a>
<ul>
<LI> <A HREF="http://www.cs.ubc.ca/~murphyk/Software/BNT/bnt.html"> Bayesian Network Toolbox (for Matlab) </A>
<LI> <A HREF="http://www.autonlab.org/tutorials/naive.html"> "Naive Bayesian" tutorial </A>
<LI> <A HREF="http://en.wikipedia.org/wiki/Three_Prisoners_Problem"> Example: three prisoners problem </A>
<LI> <A HREF="http://en.wikipedia.org/wiki/Monty_Hall_problem"> Example: Monty Hall problem </A>
</ul>
<li> More statistics and Bayesian links from George:
<ul>
<LI> <A HREF="http://astrostatistics.psu.edu/">
Center for Astrostatistics @ PSU </A>
<LI> <A HREF="http://astrostatistics.psu.edu/biblio.html">
Statistics bibliography @ PSU </A>
<LI> <A HREF="http://omega.math.albany.edu:8008/JaynesBook.html">
E.T. Jaynes's book "Probability Theory: The Logic of Scicence" </A>
* <A HREF="Jaynes-book.pdf"> Here </A> is a local copy (pdf)
<LI> <A HREF="http://bayes.wustl.edu/">
More Bayesian links </A>
</ul>
</ul><p>
<! --------------------------------------------------------------------------->
<li> March 3: Bayesian data modeling and analysis (Jewell)
<ul>
<li> <a href="http://www.astro.caltech.edu/~george/aybi199/Lec16_Jewell.pdf"> Jeff's slides (pdf) </a>
<li> More Bayesian links from Jeff:
<ul>
<LI> <A HREF="http://www.astro.cornell.edu/staff/loredo/bayes/">
Tom Loredo's BIPS (Bayesian Inference for the Physical Sciences) -
lots of good links and resources </A>
<LI> <A HREF="http://www.inference.phy.cam.ac.uk/is/">
The Inference Group at Cavendish </A>
<LI> <A HREF="http://www.inference.phy.cam.ac.uk/mackay/itila/book.html">
David MacKay's book "Information Theory, Inference, and Learning Algorithms" </A>
<LI> <A HREF="http://www.statslab.cam.ac.uk/~mcmc/">
Markov Chain Monte Carlo (MCMC) preprint server </A>
<LI> <A HREF="http://civs.stat.ucla.edu/MCMC/MCMC_tutorial.htm">
MCMC tutorial from UCLA </A>
</ul>
</ul><p>
<! --------------------------------------------------------------------------->
<li> March 5: Nonparametric Bayes and Gaussian Processes (Moghaddam)
<ul>
<li> <a href="http://www.astro.caltech.edu/~george/aybi199/Lec17_Moghaddam.pdf"> Baback's slides (pdf) </a>
<li> More true Bayesian religion from Reverend Baback:
<ul>
<LI> <A HREF="http://www.gaussianprocess.org/gpml/">
C. Rasmussen & K. Williams, "Gaussian Processes for Machine Learning" (book download) </A>
<LI> <A HREF="http://www.math.umass.edu/~lavine/whatisbayes.pdf">
M. Lavine, "What is Bayesian statistics and why everything else is wrong" </A> *
<A HREF="Lavine_whatisbayes.pdf"> local pdf file </A>
<LI> <A HREF="http://www.annals.org/cgi/reprint/130/12/995.pdf">
S. Goodman, "Toward Evidence-Based Medical Statistics. 1: The P Value Fallacy", Ann. Intern. Med., 130, 995 (1999) </A>
<LI> <A HREF="http://www.annals.org/cgi/reprint/130/12/1005.pdf">
S. Goodman, "Toward Evidence-Based Medical Statistics. 2. The Bayes Factor", Ann. Intern. Med., 130, 1005 (1999) </A>
<LI> <A HREF="http://www.stat.cmu.edu/~fienberg/fienberg-BA-06-Bayesian.pdf">
S. Fienberg, "When Did Bayesian Inference Become 'Bayesian'?", Bayesian Analysy, 1, 1 (2006) </A> (a historical account about the rise of the Bayesians...)
<LI> <A HREF="http://www.stat.columbia.edu/~gelman/blog/">
A. Gelman's blog "Statistical Modeling, Causal Inference, and Social Science" </A>
<LI> Baback also recommends <A HREF="http://www.amazon.com/Data-Analysis-Bayesian-Devinderjit-Sivia/dp/0198568320">
this book </A> as an excellent *short* Bayesian primer
</ul>
</ul><p>
<! --------------------------------------------------------------------------->
<li> March 10: Graphical models and Bayes networks (Heckerman)
<ul>
<li> <a href="http://www.astro.caltech.edu/~george/aybi199/Lec18_Heckerman.pdf"> David's slides (pdf) </a>
<LI> <A HREF="http://research.microsoft.com/en-us/um/people/heckerman/"> Dr. Heckerman's webpage </A> (contains links to BN tutorials and science examples)
<LI> <A HREF="Heckerman_BNtutorial.pdf"> BN Learning Tutorial </a> (local pdf file)
</ul><p>
<! --------------------------------------------------------------------------->
<li> Apr. 2, 7: Semantic Web (Graham)
<ul>
<li> <a href="http://www.astro.caltech.edu/~george/aybi199/Graham_Semantics1.pdf"> Matthew's slides, part I (pdf) </a>
<li> <a href="http://www.astro.caltech.edu/~george/aybi199/Graham_Semantics2.pdf"> Matthew's slides, part II (pdf) </a>
</ul><p>
<li> Apr. 14, 16: Matlab: introduction, scientific examples (Donalek)
<ul>
<li> <a href="http://www.astro.caltech.edu/~george/aybi199/Donalek_Matlab.pdf"> Ciro's slides (pdf) </a>
<ul>
<li> Examples: <a href="http://www.astro.caltech.edu/~george/aybi199/matlab_class_1.m"> matlab_class_1.m </a> * <a href="http://www.astro.caltech.edu/~george/aybi199/matlab_class.m"> matlab_class.m </a> *
<a href="http://www.astro.caltech.edu/~george/aybi199/stat.m"> stat.m </a> *
<a href="http://www.astro.caltech.edu/~george/aybi199/coin_count.m"> coin_count.m </a>
<li> <a href="http://www.mathworks.com/support/">
Matlab online Documentation</a>
<li> <a href="http://www.math.ucsd.edu/~bdriver/21d-s99/matlab-primer.html">
Matlab Primer (old but still good)</a>
<li> <a href="http://www.ncrg.aston.ac.uk/netlab/index.php">
Netlab: Neural Network Package</a>
<li> <a href="http://www.cis.hut.fi/projects/somtoolbox/">
SOM: Self Organizing Maps</a>
<li> <a href="http://www.cs.ubc.ca/~murphyk/Software/BNT/bnt.html">
Bayesian Network Toolbox</a>
</ul>
</ul><p>
<li> Apr. 21, 23: Web Services (Williams)
<ul>
<li> <a href="http://www.astro.caltech.edu/~george/aybi199/Williams_websevices1.pdf"> Roy's slides, part I: Django (pdf) </a>
<li> <a href="http://www.astro.caltech.edu/~george/aybi199/Williams_websevices2.pdf"> Roy's slides, part II: Web services in the Cloud, and VO (pdf) </a>
<ul>
<li> <a href=http://djangoproject.com>
First reference for Django: Download, tutorial, documentation</a>
<li> <a href=http://djangobook.com>
Comprehensive book about Django</a>
<li> <a href=http://djangosnippets.org>
Cookbook and Wiki</a>
<li> <a href=http://code.google.com/appengine/>
Google Appengine Cloud Computing</a>
<li> <a href=http://aws.amazon.com/ec2/>
Amazon Elastic Compute Cloud</a>
<li> <a href=http://code.google.com/appengine/articles/django.html>
Running Django on Google App Engine</a>
<li> <a href=http://thomas.broxrost.com/2008/04/08/django-on-google-app-engine/>
Django on Google App Engine in 13 simple steps</a>
<li> <a href=http://skyalert.org>
Skyalert</a>
<li> <a href=http://us-vo.org/>
US National Virtual Observatory</a>
</ul>
</ul><p>
<li> Apr. 28: Bayesian Methods - A Refresher (Moghaddam)
<ul>
<li> <a href="http://www.astro.caltech.edu/~george/aybi199/Moghaddam_Bayesian_refresher.pdf"> Baback's slides (pdf) </a>
<ul>
<li> <a href="http://research.microsoft.com/en-us/um/people/cmbishop/PRML/index.htm"> Pattern Recognition and Machine Learning book on line </a>
<li> See also the links from Bayesian lectures in the first term, below
</ul>
</ul><p>
<li> May 5, 7: R package for statistics (Mahabal)
<ul>
<li> <a href="http://www.astro.caltech.edu/~george/aybi199/Mahabal_R1.pdf"> Ashish's slides, part I (pdf) </a>
<li> <a href="http://www.astro.caltech.edu/~george/aybi199/Mahabal_R2.pdf"> Ashish's slides, part II (pdf) </a>
</ul><p>
<li> May 12, 14: Mathematica (Pepke)
<ul>
<li> <a href="http://www.astro.caltech.edu/~george/aybi199/Pepke_Mathematica1.nb"> Shirley's Mathematica notebook, part I (nb file) </a>
<li> <a href="http://www.astro.caltech.edu/~george/aybi199/Pepke_Mathematica2.nb"> Shirley's Mathematica notebook, part II (nb file) </a>
<ul>
<li> <a href="http://reference.wolfram.com/mathematica/guide/Mathematica.html"> Mathematica online help </a>
<li> <a href="http://www.wolfram.com/broadcast/#Tutorials"> Wolfram tutorials </a>
<li> <a href="http://demonstrations.wolfram.com"> Wolfram demos </a>
</ul>
</ul><p>
<li> May 18: Image processing (Cunha)
<ul>
<li> <a href="http://www.astro.caltech.edu/~george/aybi199/Cunha_improc.pdf"> Alex's slides (pdf) </a>
<ul>
<li> <a href="http://netpbm.sourceforge.net"> Netpbm package </a>
<li> <a href="http:// http://www.imagemagick.org"> ImageMagick </a>
<li> <a href=" http://mathworks.com/products/image"> Matlab Image Processing Toolbox </a>
<li> <a href="http://www.gimp.org"> Gimp (~ Photoshop) </a>
<li> <a href=" http://rsb.info.nih.gov/ij"> ImageJ / Fiji </a>
</ul>
</ul><p>
<li> May 26: Numerical libraries and tools (Petzold)
<ul>
<li> <a href="http://www.astro.caltech.edu/~george/aybi199/Petzold_numlib.pdf"> Linda's slides (pdf) </a>
</ul><p>
<li> May 28: Computational science and engineering (Stalzer)
<ul>
<li> <a href="http://www.astro.caltech.edu/~george/aybi199/Stalzer.pdf"> Mark's slides (pdf) </a>
</ul><p>
</ul>
<p>
<a href="http://escience.caltech.edu/esci101/"> An even older class website (Fall 2007) </a>
<br> <p>
</h3>