{"id":50,"date":"2019-09-28T17:46:08","date_gmt":"2019-09-28T17:46:08","guid":{"rendered":"https:\/\/my.dev.vanderbilt.edu\/cs4269aiproject\/?page_id=50"},"modified":"2022-01-21T15:02:30","modified_gmt":"2022-01-21T15:02:30","slug":"resources","status":"publish","type":"page","link":"https:\/\/my.dev.vanderbilt.edu\/cs4269aiproject\/resources\/","title":{"rendered":"Resources"},"content":{"rendered":"<p><span style=\"color: #0000ff\"><strong>UNDER CONSTRUCTION<\/strong><\/span><\/p>\n<p>Poole and Mackworth textbook: <a href=\"https:\/\/artint.info\/\">https:\/\/artint.info\/<\/a><\/p>\n<p>https:\/\/www.heardspace.org<\/p>\n<p>http:\/\/faculty.virginia.edu\/baygame\/<\/p>\n<ul>\n<li>Read Mark O. Riedl and Vadim Bulitko (2013). Interactive Narrative:<br \/>\nAn Intelligent Systems Approach, AI Magazine, Spring Issue, 67\u201477. https:\/\/www.aaai.org\/ojs\/index.php\/aimagazine\/article\/view\/2449<\/li>\n<li>Axelrod, Robert. 1984. The Evolution of Cooperation. New York: Basic Books. Adaptation retrieved from http:\/\/www-ee.stanford.edu\/~hellman\/Breakthrough\/book\/pdfs\/axelrod.pdf<\/li>\n<\/ul>\n<h1>SELECTED READINGS: CS 4269 &#8211; Spring 2019 (Kunda)<\/h1>\n<h2>Professional topics<\/h2>\n<p style=\"padding-left: 30px\">\u00b7 <strong>Professional ethics<\/strong><\/p>\n<p style=\"padding-left: 60px\">o ACM code of ethics https:\/\/www.acm.org\/code-of-ethics<\/p>\n<p style=\"padding-left: 60px\">o Duhigg article on Google teams &#8211; Teamwork and psychological safety https:\/\/www.nytimes.com\/2016\/02\/28\/magazine\/what-google-learned-from-its-quest-to-build-the-perfect-team.html<\/p>\n<p style=\"padding-left: 60px\">o Leveson article on Therac 25 &#8211; Computer software disaster http:\/\/sunnyday.mit.edu\/papers\/therac.pdf<\/p>\n<p style=\"padding-left: 60px\">o &#8220;The perks are great&#8221; article &#8211; Finding an ethical company to work for https:\/\/www.wired.com\/2016\/05\/the-perks-are-great-just-dont-ask-us-what-we-do\/<\/p>\n<p style=\"padding-left: 60px\">o Ted Chiang &#8211; Silicon Valley Is Turning Into Its Own Worst Fear https:\/\/www.buzzfeednews.com\/article\/tedchiang\/the-real-danger-to-civilization-isnt-ai-its-runaway<\/p>\n<p style=\"padding-left: 60px\">o Marketplace &#8211; The Price of Profits https:\/\/www.marketplace.org\/topics\/price-profits<\/p>\n<p style=\"padding-left: 60px\">o Why Companies Are Becoming B Corporations https:\/\/hbr.org\/2016\/06\/why-companies-are-becoming-b-corporations<\/p>\n<p style=\"padding-left: 30px\">\u00b7 <strong>Human subjects research<\/strong><\/p>\n<p style=\"padding-left: 60px\">o Leetaru 2016 &#8211; article on research ethics in the era of ML and big data https:\/\/www.forbes.com\/sites\/kalevleetaru\/2016\/06\/17\/are-research-ethics-obsolete-in-the-era-of-big-data\/#ba019aa7aa3d<\/p>\n<p style=\"padding-left: 60px\">o Kramer et al 2014 &#8211; Facebook emotion manipulation study https:\/\/www.pnas.org\/content\/111\/24\/8788 (and &#8220;editorial expression of concern&#8221; from the journal PNAS, a &#8220;top&#8221; journal, very unusual) https:\/\/www.pnas.org\/content\/111\/29\/10779.1<\/p>\n<p style=\"padding-left: 30px\">\u00b7 <strong>Writing and communication<\/strong><\/p>\n<p style=\"padding-left: 60px\">o Kunda \u2013 Guide to Writing with Figures<\/p>\n<h2>General AI and machine learning<\/h2>\n<p style=\"padding-left: 30px\">\u00b7 <strong>AI = representations + search<\/strong><\/p>\n<p style=\"padding-left: 60px\">o Newell and Simon Turing award lecture (in article form) http:\/\/citeseerx.ist.psu.edu\/viewdoc\/download?doi=10.1.1.104.2482&amp;rep=rep1&amp;type=pdf<\/p>\n<p style=\"padding-left: 30px\">\u00b7 <strong>Machine learning all topics<\/strong><\/p>\n<p style=\"padding-left: 60px\">o Online lectures by Isbell and Littman (Udacity course) https:\/\/www.udacity.com\/course\/machine-learning&#8211;ud262<\/p>\n<h2>Supervised learning &#8211; General methods<\/h2>\n<p style=\"padding-left: 30px\">\u00b7<strong> Basic methodology<\/strong><\/p>\n<p style=\"padding-left: 60px\">o Understanding feature engineering &#8211; Supervised learning pipeline, and working with features https:\/\/towardsdatascience.com\/understanding-feature-engineering-part-1-continuous-numeric-data-da4e47099a7b<\/p>\n<p style=\"padding-left: 60px\">o Train\/test split and cross validation https:\/\/towardsdatascience.com\/train-test-split-and-cross-validation-in-python-80b61beca4b6<\/p>\n<p style=\"padding-left: 60px\">o Confusion matrices and accuracy metrics https:\/\/ibug.doc.ic.ac.uk\/media\/uploads\/documents\/ml-lecture3-2014.pdf<\/p>\n<p style=\"padding-left: 60px\">o Provost and Fawcett 1997 &#8211; Paper on ROC curves and limitations https:\/\/www.aaai.org\/Papers\/KDD\/1997\/KDD97-007.pdf<\/p>\n<p style=\"padding-left: 30px\">\u00b7 <strong>Data leakage<\/strong> (contaminating test data with training data)<\/p>\n<p style=\"padding-left: 60px\">o Data leakage in ML &#8211; high level overview of the problem https:\/\/machinelearningmastery.com\/data-leakage-machine-learning\/<\/p>\n<p style=\"padding-left: 60px\">o Kaufman et al 2011 &#8211; technical discussion of leakage, what it is, and how to avoid it https:\/\/citeseerx.ist.psu.edu\/viewdoc\/download?doi=10.1.1.365.7769&amp;rep=rep1&amp;type=pdf<\/p>\n<p style=\"padding-left: 60px\">o ICML 2013 whale challenge &#8211; famous example of data leakage in a Kaggle contest https:\/\/www.kaggle.com\/c\/the-icml-2013-whale-challenge-right-whale-redux\/discussion\/4865#25839<\/p>\n<p style=\"padding-left: 60px\">o Story of a bad train\/test split &#8211; another interesting (and subtle) example https:\/\/engineering.taboola.com\/story-of-bad-train-test-split\/<\/p>\n<p style=\"padding-left: 30px\">\u00b7<strong> Features<\/strong><\/p>\n<p style=\"padding-left: 60px\">o Text data &#8211; pre-processing and feature extraction https:\/\/towardsdatascience.com\/understanding-feature-engineering-part-3-traditional-methods-for-text-data-f6f7d70acd41<\/p>\n<h2>Decision trees<\/h2>\n<p style=\"padding-left: 30px\">\u00b7 <strong>Overview<\/strong><\/p>\n<p style=\"padding-left: 60px\">o Mitchell 1997 chapter on decision trees, including pruning<\/p>\n<p style=\"padding-left: 60px\">o ID3 algorithm from Isbell and Littman lecture notes<\/p>\n<p style=\"padding-left: 60px\">o Random forests https:\/\/towardsdatascience.com\/the-random-forest-algorithm-d457d499ffcd<\/p>\n<p style=\"padding-left: 30px\">\u00b7 <strong>Case study on decision tress and autism diagnosis<\/strong><\/p>\n<p style=\"padding-left: 60px\">o Wall et al &#8211; two papers that did not follow good ML practices https:\/\/journals.plos.org\/plosone\/article?id=10.1371\/journal.pone.0043855 https:\/\/www.nature.com\/articles\/tp201210<\/p>\n<p style=\"padding-left: 60px\">o Bone et al &#8211; analysis of the above Wall et al papers, including recommendations for doing solid applied ML work https:\/\/link.springer.com\/article\/10.1007\/s10803-014-2268-6<\/p>\n<h2>Neural networks<\/h2>\n<p style=\"padding-left: 30px\">\u00b7 <strong>Overview<\/strong><\/p>\n<p style=\"padding-left: 60px\">o Nielsen deep learning textbook &#8211; Perceptrons, multilayer networks, backpropagation, and deep networks http:\/\/neuralnetworksanddeeplearning.com\/<\/p>\n<p style=\"padding-left: 60px\">o Krishevsky et al 2012 &#8211; the famous (infamous?) ImageNet paper (first big deep learning success) https:\/\/papers.nips.cc\/paper\/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf<\/p>\n<h2>Reinforcement learning<\/h2>\n<p style=\"padding-left: 30px\">\u00b7 <strong>Overview<\/strong><\/p>\n<p style=\"padding-left: 60px\">o Silver et al 2016 &#8211; famous paper on AlphaGo, first AI program to &#8220;beat&#8221; humans at the game of Go https:\/\/www.nature.com\/articles\/nature16961<\/p>\n<p><strong>Unsupervised learning<\/strong><\/p>\n<p style=\"padding-left: 30px\">\u00b7<strong> Overview<\/strong><\/p>\n<p style=\"padding-left: 60px\">o Jain 2010 &#8211; Data clustering &#8211; 50 years beyond K-means https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0167865509002323<\/p>\n","protected":false},"excerpt":{"rendered":"<p>UNDER CONSTRUCTION Poole and Mackworth textbook: https:\/\/artint.info\/ https:\/\/www.heardspace.org http:\/\/faculty.virginia.edu\/baygame\/ Read Mark O. Riedl and Vadim Bulitko (2013). Interactive Narrative: An Intelligent Systems Approach, AI Magazine, Spring Issue, 67\u201477. https:\/\/www.aaai.org\/ojs\/index.php\/aimagazine\/article\/view\/2449 Axelrod, Robert. 1984. The Evolution of Cooperation. New York: Basic Books. &hellip; <a href=\"https:\/\/my.dev.vanderbilt.edu\/cs4269aiproject\/resources\/\">Continue reading <span class=\"meta-nav\">&rarr;<\/span><\/a><\/p>\n","protected":false},"author":633,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-50","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/my.dev.vanderbilt.edu\/cs4269aiproject\/wp-json\/wp\/v2\/pages\/50","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/my.dev.vanderbilt.edu\/cs4269aiproject\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/my.dev.vanderbilt.edu\/cs4269aiproject\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/my.dev.vanderbilt.edu\/cs4269aiproject\/wp-json\/wp\/v2\/users\/633"}],"replies":[{"embeddable":true,"href":"https:\/\/my.dev.vanderbilt.edu\/cs4269aiproject\/wp-json\/wp\/v2\/comments?post=50"}],"version-history":[{"count":8,"href":"https:\/\/my.dev.vanderbilt.edu\/cs4269aiproject\/wp-json\/wp\/v2\/pages\/50\/revisions"}],"predecessor-version":[{"id":698,"href":"https:\/\/my.dev.vanderbilt.edu\/cs4269aiproject\/wp-json\/wp\/v2\/pages\/50\/revisions\/698"}],"wp:attachment":[{"href":"https:\/\/my.dev.vanderbilt.edu\/cs4269aiproject\/wp-json\/wp\/v2\/media?parent=50"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}