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Statistics, Data Mining, and Machine Learning in Astronomy
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Statistics, Data Mining, and Machine Learning in Astronomy: A Practical Python Guide for the Analysis of Survey Data

Željko Ivezic, Andrew J. Connolly, Jacob T VanderPlas, and Alexander Gray

Abstract

As telescopes, detectors, and computers grow ever more powerful, the volume of data at the disposal of astronomers and astrophysicists will enter the petabyte domain, providing accurate measurements for billions of celestial objects. This book provides a comprehensive and accessible introduction to the cutting-edge statistical methods needed to efficiently analyze complex data sets from astronomical surveys such as the Panoramic Survey Telescope and Rapid Response System, the Dark Energy Survey, and the upcoming Large Synoptic Survey Telescope. It serves as a practical handbook for graduate st ... More

Keywords: telescopes, detectors, computers, petabyte domain, statistical methods, astronomical surveys, astronomy, astrophysics, Python code

Bibliographic Information

Print publication date: 2014 Print ISBN-13: 9780691151687
Published to Princeton Scholarship Online: October 2017 DOI:10.23943/princeton/9780691151687.001.0001

Authors

Affiliations are at time of print publication.

Željko Ivezic, author
University of Washington

Andrew J. Connolly, author

Jacob T VanderPlas, author

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