The Online Books Page

Machine learning -- Mathematical models

See also what's at your library, or elsewhere.

• Machine learning
• Mathematical models

• Gaussian Processes fo Machine Learning (online edition; originally published Cambridge, MA and London: MIT Press, c2006), by Carl Edward Rasmussen and Christopher K. I. Williams (PDF with commentary at gaussianprocess.org)

Items below (if any) are from related and broader terms.

• 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)

• 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)

• Journal of Machine Learning Research (2000-) (full serial archives)

• Learning Deep Architectures for AI (c2009), by Yoshua Bengio (PDF at Wayback Machine)

• 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)

• Boosting: Foundations and Algorithms (Cambridge, MA and London: MIT Press, c2012), by Robert E. Schapire and Yoav Freund (HTML with commentary at MIT Press)

• Boosting: Foundations and Algorithms (Cambridge, MA and London: MIT Press, c2012), by Robert E. Schapire and Yoav Freund (HTML with commentary at MIT Press)

• An Introduction to Statistical Learning, With Applications in R (corrected first edition and second edition; 2017 and 2021), by Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani (PDF with commentary at statlearning.com)
• Modeling with Data (Princeton : Princeton University Press, c2009), by Ben Klemens (PDF with commentary at modelingwithdata.org)

• Physical Modeling in MATLAB, by Allen Downey (multiple formats at Green Tea Press)

• An Introduction to Statistical Learning, With Applications in R (corrected first edition and second edition; 2017 and 2021), by Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani (PDF with commentary at statlearning.com)

• Modeling and Simulation in Python (version 3.4.3; Needham, MA: Green Tea Press, 2017), by Allen Downey (PDF with commentary at Green Tea Press)
• The Nature of Code (c2012), by Daniel Shiffman, ed. by Shannon Fry, illust. by Zannah Marsh (illustrated HTML with commentary at natureofcode.com)
• A Practical Manual on the Monte Carlo Method for Random Walk Problems (Los Alamos, NM: Los Alamos Scientific Laboratory of the University of California, 1957), by E. D. Cashwell and C. J. Everett, contrib. by O. W. Rechard (page images at HathiTrust)

• Game Theory (second edition, c2018), by Giacomo Bonanno (PDF with commentary at UC Davis)
• Economics and Language: Five Essays (2000), by Ariel Rubinstein (PDF in Israel)
• Economic Fables (Cambridge, UK: Open Book Publishers, c2012), by Ariel Rubinstein
  • PDF and HTML with commentary at Open Book Publishers
  • page images at Google
• The Strategic Constitution (prepublication version, 1999), by Robert Cooter (PDF at bepress.com)
• Modeling Bounded Rationality (1998), by Ariel Rubinstein (PDF in Israel)
• Rules, Games, and Common-Pool Resources (Ann Arbor: University of Michigan Press, c1994), ed. by Elinor Ostrom, Roy Gardner, and James Walker (page images at HathiTrust)
• Bargaining and Markets (electronic edition; with corrections from 1990 edition), by Martin J. Osborne and Ariel Rubinstein (PDF files with commentary at Toronto)

• Statistical Learning With Sparsity: The Lasso and Generalizations (corrected online edition, 2016), by Trevor Hastie, Robert Tibshirani, and Martin Wainwright (PDF with commentary at Stanford)

• A Practical Manual on the Monte Carlo Method for Random Walk Problems (Los Alamos, NM: Los Alamos Scientific Laboratory of the University of California, 1957), by E. D. Cashwell and C. J. Everett, contrib. by O. W. Rechard (page images at HathiTrust)

• Determination of Azimuth Angle at Burnout for Placing a Satellite Over a Selected Earth Position (NASA Technical Note D-233; 1960), by T. H. Skopinski and Katherine G. Johnson (page images at HathiTrust)

• Determination of Azimuth Angle at Burnout for Placing a Satellite Over a Selected Earth Position (NASA Technical Note D-233; 1960), by T. H. Skopinski and Katherine G. Johnson (page images at HathiTrust)

• Bank Management and Portfolio Behavior (Cowles Foundation monograph #25; New Haven and London: Yale University Press, 1975), by Donald D. Hester and James L. Pierce (PDF at Yale)

• Numerical Methods and Modeling for Chemical Engineers (New York et al.: Wiley, c1984), by Mark E. Davis (PDF files at Caltech)

• Urban Travel Demand: A Behavioral Analysis, by Thomas A. Domencich and Daniel L. McFadden (PDF files at Berkeley)

• GOALS (Global Ocean-Atmosphere-Land System) for Predicting Seasonal-to-Interannual Climate (1994), by National Research Council Climate Research Committee (page images with commentary at NAP)

• Urban Travel Demand: A Behavioral Analysis, by Thomas A. Domencich and Daniel L. McFadden (PDF files at Berkeley)

• Economic Theory of Teams (Cowles Foundation monograph #22; New Haven and London: Yale University Press, 1972), by Jacob Marschak and Roy Radner (PDF at Yale)

• The Theoretical Foundation of Dendritic Function: Selected Papers of Wilfrid Rall With Commentaries (Cambridge, MA and London: MIT Press, c1995), by Wilfrid Rall, ed. by Idan Segev, John Rinzel, and Gordon M. Shepherd (PDF with commentary at MIT Press)

• Dispersion Simulation Techniques for Assessing the Air Pollution Impacts of Ground Transportation Systems (Chicago: Illinois Institute for Environmental Quality, 1974), by L. J. Habegger, T. D. Wolsko, J. E. Camaioni, David A. Kellermeyer, and Peter A. Dauzvardis (page images at HathiTrust)

• Global Models, World Futures, and Public Policy: A Critique (1982), by United States Congress Office of Technology Assessment
  • page images at HathiTrust
  • PDF files at Princeton

• Global Models, World Futures, and Public Policy: A Critique (1982), by United States Congress Office of Technology Assessment
  • page images at HathiTrust
  • PDF files at Princeton

• Intellectual Trespassing as a Way of Life: Essays in Philosophy, Economics, and Mathematics (1995), by David P. Ellerman (PDF with commentary at ellerman.org)

• Family Planning and Family Size Determination: The Evidence From Seven Latin American Cities (Gainesville: University Presses of Florida, 1976), by Manuel J. Carvajal and David T. Geithman (page images at Florida)

• Principles of Control Systems Engineering (New York et al.: McGraw-Hill Book Co., 1960), by Vincent Del Toro and Sydney R. Parker (page images at HathiTrust)
• Analytical Design of Linear Feedback Controls (New York: J. Wiley and Sons; London: Chapman and Hall, c1957), by George C. Newton, Leonard A. Gould, and James F. Kaiser (page images at HathiTrust)

More items available under broader and related terms at left.