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Browsing Library of Congress Call Numbers : "Q224.5 .M44 2019" to "Q334.7 .C45 2022" (Overview; Include extended shelves)

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Call number Item
Q Science (Go to start of category)
Q224.5 .M44 2019 [Info] Science Communication Online: Engaging Experts and Publics on the Internet (Columbus, OH: Ohio State University Press, 2019), by Ashley Rose Mehlenbacher (PDF at Ohio State)
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
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
Q295 .G64 1994 [Info] Chaotic Logic: Language, Thought and Reality From the Perspective of Complex Systems Science (prepublication version), by Ben Goertzel (HTML at
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
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
Q325.5 .G6 [Info] Deep Learning (prepublication version; 2016), by Ian Goodfellow, Yoshua Bengio, and Aaron Courville (illustrated HTML with commentary at
Q325.5 .G68 2020 [Info] Probabilistic Machine Learning for Civil Engineers (prepublication version; 2020), by James-A. Goulet (PDF files with commentary at
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
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
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
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)

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