Statistics, Data Mining, and Machine Learning in Astronomy: A Practical Python Guide for the Analysis of Survey Data, Updated Edition - Hardcover
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Availability:In StockContributor:Zeljko Ivezic, Andrew J. Connolly, Jacob T. VanderPlasSeries:Princeton Modern Observational Astronomy #8Publish date:2019-12-03Pages:560
Language:EnglishPublisher:Princeton University PressISBN-13:9780691198309ISBN-10:691198306UPC:9780691198309Book Category:ScienceBook Subcategory:Space Science, PhysicsBook Topic:Astronomy, Astrophysics, Mathematical & ComputationalSize:10.10 x 7.20 x 1.60 inchesWeight:2.8528Product ID:SCTFE6N0A3
Statistics, Data Mining, and Machine Learning in Astronomy is the essential introduction to the statistical methods needed to analyze complex data sets from astronomical surveys such as the Panoramic Survey Telescope and Rapid Response System, the Dark Energy Survey, and the Large Synoptic Survey Telescope. Now fully updated, it presents a wealth of practical analysis problems, evaluates the...
Language:EnglishPublisher:Princeton University PressISBN-13:9780691198309ISBN-10:691198306UPC:9780691198309Book Category:ScienceBook Subcategory:Space Science, PhysicsBook Topic:Astronomy, Astrophysics, Mathematical & ComputationalSize:10.10 x 7.20 x 1.60 inchesWeight:2.8528Product ID:SCTFE6N0A3
Zeljko Ivezic is professor of astronomy at the University of Washington. Andrew J. Connolly is professor of astronomy at the University of Washington. Jacob T. VanderPlas is a software engineer at Google. Alexander Gray is vice president of AI science at IBM.
Publisher: Princeton University Press
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Revised Edition
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