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

Author: Željko Ivezić
Publisher: Princeton, N.J. : Princeton Univ. Press, 2014.
Series: Princeton series in modern observational astronomy
Edition/Format:   Print book : EnglishView all editions and formats
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Provides an 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  Read more...

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Document Type: Book
All Authors / Contributors: Željko Ivezić
ISBN: 0691151687 9780691151687
OCLC Number: 891565870
Description: x, 540 Seiten : Illustrationen, Diagramme.
Contents: *Frontmatter, pg. i*Contents, pg. v*Preface, pg. ix*1. About the Book and Supporting Material, pg. 3*2. Fast Computation on Massive Data Sets, pg. 43*3. Probability and Statistical Distributions, pg. 69*4. Classical Statistical Inference, pg. 123*5. Bayesian Statistical Inference, pg. 175*6. Searching for Structure in Point Data, pg. 249*7. Dimensionality and Its Reduction, pg. 289*8. Regression and Model Fitting, pg. 321*9. Classification, pg. 365*10. Time Series Analysis, pg. 403*A. An Introduction to Scientific Computing with Python, pg. 471*B. AstroML: Machine Learning for Astronomy, pg. 511*C. Astronomical Flux Measurements and Magnitudes, pg. 515*D. SQL Query for Downloading SDSS Data, pg. 519*E. Approximating the Fourier Transform with the FFT, pg. 521*Visual Figure Index, pg. 527*Index, pg. 533
Series Title: Princeton series in modern observational astronomy
Responsibility: Željko Ivezić ...

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Winner of the 2016 IAA Outstanding Publication Award, International Astrostatistics Association "Ivezic and colleagues at the University of Washington and the Georgia Institute of Technology have Read more...

 
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