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Browsing Library of Congress Call Numbers : "Q225 .H45 1991" to "Q335 .A74 2002" (Overview; Include extended shelves)

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:
Call number Item
Q Science (Go to start of category)
Q225 .H45 1991 [Info] Headline News, Science Views (1991), ed. by David Jarmul (page images with commentary at NAP)
Q225 .H45 1993 [Info] Headline News, Science Views II (1993), ed. by David Jarmul (page images with commentary at NAP)
Q225.2.U6 H378 [Info] Worlds Apart: How the Distance Between Science and Journalism Threatens America's Future, by Jim Hartz and Rick Chappell (PDF at Freedom Forum)
Q295 .E33 1987 [Info] A Fuller Explanation: The Synergetic Geometry of R. Buckminster Fuller (1987 edition), by Amy C. Edmondson (HTML at pauladaunt.com)
Q295 .E33 2007 [Info] A Fuller Explanation: The Synergetic Geometry of R. Buckminster Fuller (Pueblo, CO: EmergentWorld Press, c2007), by Amy C. Edmondson (page images at Google)
Q295 .F84 [Info] Synergetics: Explorations in the Geometry of Thinking (electronic edition), by R. Buckminster Fuller and E. J. Applewhite (HTML at rwgrayprojects.com)
Q295 .G64 1994 [Info] Chaotic Logic: Language, Thought and Reality From the Perspective of Complex Systems Science (prepublication version), by Ben Goertzel (HTML at goertzel.org)
Q300 .M688 [Info] Journal of Machine Learning Research (2000-) (full serial archives)
Q325.5 .B36 2019 [Info] Fairness and Machine Learning: Limitations and Opportunities (prepublication version; 2019), by Solon Barocas, Moritz Hardt, and Arvind Narayanan (HTML with commentary at fairmlbook.org)
Q325.5 .D45 2020 [Info] Mathematics for Machine Learning (prepublication free online edition; 2020), by Marc Peter Deisenroth, A. Aldo Faisal, and Cheng Soon Ong (PDF with commentary at github.io)
Q325.5 .G6 [Info] Deep Learning (prepublication version; 2016), by Ian Goodfellow, Yoshua Bengio, and Aaron Courville (illustrated HTML with commentary at deeplearningbook.org)
Q325.5 .G68 2020 [Info] Probabilistic Machine Learning for Civil Engineers (prepublication version; 2020), by James-A. Goulet (PDF files with commentary at polymtl.ca)
Q325.5 .H364 2020 [Info] Graph Representation Learning (prepublication version, 2020), by William L. Hamilton (PDF at McGill)
Q325.5 .M324 [Info] Machine Learning, Neural and Statistical Classification, ed. by Donald Michie, D. J. Spiegelhalter, and Charles C. Taylor (PDF and gzipped Postscript in the UK)
Q325.5 .M58 1997 [Info] Machine Learning (main text c1997; additional chapters c2017), by Tom M. Mitchell (PDF with commentary at CMU)
Q325.5 .M64 2018 [Info] Foundations of Machine Learning (second edition; Cambridge, MA and London: MIT Press, c2018), by Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalkar (HTML at ublish.com)
Q325.5 .P48 2017 [Info] Elements of Causal Inference: Foundations and Learning Algorithms (Cambridge, MA and London: MIT Press, c2017), by Jonas Peters, Dominik Janzing, and Bernhard Schölkopf (PDF with commentary at MIT Press)
Q325.6 .S88 [Info] Reinforcement Learning: An Introduction (first and second editions, 1998 and 2018), by Richard S. Sutton and Andrew G. Barto (HTML and PDF at incompleteideas.net)
Q325.7 .B465 2009 [Info] Learning Deep Architectures for AI (c2009), by Yoshua Bengio (PDF at Wayback Machine)
Q325.75 .H37 [Info] The Elements of Statistical Learning: Data Mining, Inference, and Prediction (second edition, 2009), by Trevor Hastie, Robert Tibshirani, and J. H. Friedman (PDF with commentary at Stanford)
Q325.75 .S33 2012 [Info] Boosting: Foundations and Algorithms (Cambridge, MA and London: MIT Press, c2012), by Robert E. Schapire and Yoav Freund (HTML with commentary at MIT Press)
Q327 .B52 2006 [Info] Pattern Recognition and Machine Learning (c2006), by Christopher M. Bishop (PDF at microsoft.com)
Q334 .J68 [Info] Journal of Artificial Intelligence Research (1993-) (full serial archives)
Q334.7 .C45 2022 [Info] Can We Trust AI? (Baltimore: Johns Hopkins University Press, c2022), by Rama Chellappa, contrib. by Eric Niiler (multiple formats with commentary at Project MUSE)
Q335 .A74 2002 [Info] Are We Spiritual Machines? Ray Kurzweil vs. the Critics of Strong A.I. (c2002), ed. by Jay W. Richards, contrib. by Ray Kurzweil, John R. Searle, Michael J. Denton, William A. Dembski, Thomas S. Ray, and George F. Gilder (at kurzweilai.net)

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