Statistics, data mining, and machine learning in astronomy

Statistics, data mining, and machine learning in astronomy: a practical Python guide for the analysis of survey data

by Connolly, Andrew, (Andrew J.) Gray, Alexander, (Alexander G.) Ivezić, Željko Vanderplas, Jacob T.

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Title Statements

  • Full title :Statistics, data mining, and machine learning in astronomy : a practical Python guide for the analysis of survey data / Željko Ivezić, Andrew J. Connolly, Jacob T. VanderPlas, and Alexander Gray.

Edition Statements

  • Publication Date:©2014

Publication Statements

The Physical Object

  • Description:x, 540 pages : : illustrations ; : 26 cm

Edition Identifiers

  • ISBN:9780691151687, 0691151687
  • oclc:ocn966354048
  • LC Classification:QB149
  • Dewey Decimal:522/.85

Table of Contents

About the book and supporting material -- Fast computation on massive data sets -- Probability and statistical distributions -- Classical statistical inference -- Bayesian statistical inference -- Searching for structure in point data -- Dimensionality and its reduction -- Regression and model fitting -- Classification -- Time series analysis -- An introduction to scientific computing with Python -- AstroML : machine learning for astronomy -- Astronomical flux measurements and magnitudes -- SQL query for downloading SDSS data -- Approximating the Fourier Transform with the FFT.

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Subjects

Astronomy -- Data processing statistical astronomy Statistique stellaire

Writers

Connolly, Andrew, (Andrew J.) Gray, Alexander, (Alexander G.) Ivezić, Željko Vanderplas, Jacob T.

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