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Filed under: Machine learning- Graph Representation Learning (prepublication version, 2020), by William L. Hamilton (PDF at McGill)
- Probabilistic Machine Learning for Civil Engineers (prepublication version; 2020), by James-A. Goulet (PDF files with commentary at polymtl.ca)
- 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)
- 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)
- Machine Learning (main text c1997; additional chapters c2017), by Tom M. Mitchell (PDF with commentary at CMU)
- Deep Learning (prepublication version; 2016), by Ian Goodfellow, Yoshua Bengio, and Aaron Courville (illustrated HTML with commentary at deeplearningbook.org)
- Bayesian Reasoning and Machine Learning (free online edition, c2014), by David Barber (PDF with commentary in the UK)
- 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)
- 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)
- Pattern Recognition and Machine Learning (c2006), by Christopher M. Bishop (PDF at microsoft.com)
- Ethics and Data Science (c2019), by Michael Kosta Loukides, Hilary Mason, and DJ Patil (HTML at oreilly.com)
- A Course in Machine Learning, by Hal Daumé (PDF with commentary at ciml.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)
- Introduction to learning machines (National Aeronautics and Space Administration; [for sale by the Clearinghouse for Federal Scientific and Technical Information, Springfield, Va.], 1970), by Jack G. Sheppard, Manned Spacecraft Center, and United States National Aeronautics and Space Administration (page images at HathiTrust)
- Sociopathic knowledge bases : correct knowledge can be harmful even given unlimited computation (Department of Computer Science, University of Illinois, 1989), by David C. Wilkins and Yong Ma (page images at HathiTrust)
- A program for the solution of a class of geometric-analogy intelligence-test questions (L.G. Hansom Field, Bedford, Massachusetts : Air Force Cambridge Research Laboratories, Office of Aerospace Research, United States Air Force, 1964., 1964), by Thomas G. Evans and Air Force Cambridge Research Laboratories (U.S.) (page images at HathiTrust)
- The unsolvability of the equivalence problem for lambda-free nondeterministic generalized machines. (L. G. Hansom Field, Bedford, Massachusetts : Air Force Cambridge Research Laboratories, Office of Aerospace Research, United States Air Force, 1968., 1968), by Thomas V. Griffiths and Air Force Cambridge Research Laboratories (U.S.) (page images at HathiTrust)
- A study of generalized machine learning (Wright-Patterson Air Force Base, Ohio : Electronic Technology Laboratory, Aeronautical Systems Division, Air Force Systems Command, United States Air Force, 1962., 1962), by E. Bryan Carne, United States. Air Force. Systems Command. Aeronautical Systems Division, and Inc Melpar (page images at HathiTrust)
Filed under: Machine learning -- Mathematical models
Filed under: Machine learning -- Mathematics
Filed under: Machine learning -- Moral and ethical aspectsFiled under: Machine learning -- Periodicals
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