Statistics, Data Mining, and Machine Learning in Astronomy

Ebook

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 students and advanced undergraduates in physics and astronomy, and as an indispensable reference for researchers.

Statistics, Data Mining, and Machine Learning in Astronomy presents a wealth of practical analysis problems, evaluates techniques for solving them, and explains how to use various approaches for different types and sizes of data sets. For all applications described in the book, Python code and example data sets are provided. The supporting data sets have been carefully selected from contemporary astronomical surveys (for example, the Sloan Digital Sky Survey) and are easy to download and use. The accompanying Python code is publicly available, well documented, and follows uniform coding standards. Together, the data sets and code enable readers to reproduce all the figures and examples, evaluate the methods, and adapt them to their own fields of interest.

  • Describes the most useful statistical and data-mining methods for extracting knowledge from huge and complex astronomical data sets
  • Features real-world data sets from contemporary astronomical surveys
  • Uses a freely available Python codebase throughout
  • Ideal for students and working astronomers
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Statistics Data Mining And Machine Learning In Astronomy


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Languange Used : en
Release Date : 2014-01-05
Publisher by : Princeton University Press

As telescopes, detectors, and computers grow ever more powerful, the volume of data at the disposal of astrono

Statistics Data Mining And Machine Learning In Astronomy


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Languange Used : en
Release Date : 2013-12-01
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Advances In Machine Learning And Data Mining For Astronomy


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Author by : Michael J. Way
Languange Used : en
Release Date : 2012-03-29
Publisher by : CRC Press

Advances in Machine Learning and Data Mining for Astronomy documents numerous successful collaborations among

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Author by : Masashi Sugiyama
Languange Used : en
Release Date : 2015-10-31
Publisher by : Morgan Kaufmann

Machine learning allows computers to learn and discern patterns without actually being programmed. When Statis

Principles And Theory For Data Mining And Machine Learning


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Languange Used : en
Release Date : 2009-07-21
Publisher by : Springer Science & Business Media

Extensive treatment of the most up-to-date topics Provides the theory and concepts behind popular and emerging

Python Data Science Handbook


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Author by : Jake VanderPlas
Languange Used : en
Release Date : 2016-11-21
Publisher by : "O'Reilly Media, Inc."

For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating,

Modern Statistical Methods For Astronomy


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Author by : Eric D. Feigelson
Languange Used : en
Release Date : 2012-07-12
Publisher by : Cambridge University Press

"Modern astronomical research is beset with a vast range of statistical challenges, ranging from reducing data

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