Breaking News: The class final be in 380380W on Saturday, 6/4, 78:30 pm. See Piazza for more details. May 24: A new version of homework 4 [v4] has be posted  be sure to use the new version.  Data today often has a geometric character, as is the case with 1D GPS traces, 2D images / videos, 3D scans / 3D models, and so on. Even nongeometric data, e.g. social networks or genomic microarrays, are often best analyzed by embedding them in a multidimensional geometric feature space. The goal of this course is to cover the rudiments of geometric and topological methods that have proven useful in the analysis of such data. The course also aims to show that there can be multiple perspectives or views on the same data, and that a particular piece of data is often best understood not alone but within a "social network" of related data sets that provide a useful context for its analysis.
This course presumes an elementary knowledge of algorithms and linear algebra. It will require four assignments (w. programming) and a final exam. These pages are maintained by Leonidas Guibas guibas@cs.stanford.edu.
