Opening Up Astronomy with Python and AstroML; SciPy 2013 Presentation

Authors: Vanderplas, Jake, University of Washington; Ivezic, Zeljko, University of Washington; Connolly, Andrew, University of Washington Track: General As astronomical data sets grow in size and complexity, automated machine learning and data mining methods are becoming an increasingly fundamental component of research in the field. The astroML project (http://astroML.github.com), first released in fall 2012, provides a common repository for practical examples of the data mining and machine learning tool