CN710 considers the systematic analysis of supervised learning systems from neural networks, statistics, and artificial intelligence. Supervised learning systems include multi-layer perceptrons (MLP), ARTMAP, support vector machines, and K-nearest neighbors (KNN). Working in collaboration, class members analyze many different algorithms and methods for pre- and post-processing data, with common benchmark problems and system evaluation criteria.


710 book reports – Fall 2008
Ben Chandler
Nassim Nicholas Taleb (2007) The Black Swan: The Impact of the Highly Improbable. Random House.
Jeff Doon
Steven Johnson (2005) Everything Bad is Good for You: How Today’s Popular Culture is Actually Making Us Smarter. Penguin.
Gary Small (2008) Surviving the Technological Alteration of the Modern Mind. HarperCollins.
Todd Hay
Judea Pearl (2000) Causality: Models, Reasoning, and Inference. Cambridge University Press.
Jeff Markowitz
Marvin L. Minsky & Seymour A. Papert (1969, 1987) Perceptrons – Expanded Edition: An Introduction to Computational Geometry. MIT Press.
Yvonne Pu
Wolfgang Maass & Christopher M. Bishop (2001) Pulsed Neural Networks. MIT Press.
Melissa St. Hilaire
Steven Strogatz (2003) Synch: The Emerging Science of Spontaneous Order. Hyperion.
John Anderson (2007) How Can the Human Mind Occur in the Physical Universe? Oxford University Press.
Charles Wong
Jared Diamond (1992) The Third Chimpanzee: The Evolution and Future of the Human Animal. Harper.
Andy Clark (2003) Natural-Born Cyborgs: Minds, Technology, and the Future of Human Intelligence. Oxford University Press.
Peifeng Zhang
Ian H. Witten & Eibe Frank (2005) Data Mining: Practical Machine Learning Tools and Techniques, Second Edition. Morgan Kaufmann.
Leah Ziph-Schatzberg
Malcolm Gladwell (2005) Blink: The Power of Thinking Without Thinking. Little, Brown.
Stephen Jay Gould (1992) Ever Since Darwin: Reflections on Natural History. W.W. Norton.