Statistics Data Mining and Machine Learning in Astronomy Book [PDF] Download

Download the fantastic book titled Statistics Data Mining and Machine Learning in Astronomy written by Željko Ivezić, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Statistics Data Mining and Machine Learning in Astronomy", which was released on 12 January 2014. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Science genre.

Summary of Statistics Data Mining and Machine Learning in Astronomy by Željko Ivezić PDF

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


Detail About Statistics Data Mining and Machine Learning in Astronomy PDF

  • Author : Željko Ivezić
  • Publisher : Princeton University Press
  • Genre : Science
  • Total Pages : 550 pages
  • ISBN : 0691151687
  • PDF File Size : 9,8 Mb
  • Language : English
  • Rating : 4/5 from 21 reviews

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Statistics, Data Mining, and Machine Learning in Astronomy

Statistics, Data Mining, and Machine Learning in Astronomy
  • Publisher : Princeton University Press
  • File Size : 31,9 Mb
  • Release Date : 12 January 2014
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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

Statistics, Data Mining, and Machine Learning in Astronomy

Statistics, Data Mining, and Machine Learning in Astronomy
  • Publisher : Princeton University Press
  • File Size : 45,8 Mb
  • Release Date : 03 December 2019
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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

Statistics, Data Mining, and Machine Learning in Astronomy

Statistics, Data Mining, and Machine Learning in Astronomy
  • Publisher : Unknown Publisher
  • File Size : 55,6 Mb
  • Release Date : 16 June 2024
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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

Advances in Machine Learning and Data Mining for Astronomy

Advances in Machine Learning and Data Mining for Astronomy
  • Publisher : CRC Press
  • File Size : 44,6 Mb
  • Release Date : 29 March 2012
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Advances in Machine Learning and Data Mining for Astronomy documents numerous successful collaborations among computer scientists, statisticians, and astronomers who illustrate the application of state-of-the-art machine learning and data mining

Advances in Machine Learning and Data Mining for Astronomy

Advances in Machine Learning and Data Mining for Astronomy
  • Publisher : CRC Press
  • File Size : 42,7 Mb
  • Release Date : 29 March 2012
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Advances in Machine Learning and Data Mining for Astronomy documents numerous successful collaborations among computer scientists, statisticians, and astronomers who illustrate the application of state-of-the-art machine learning and data mining

Astrostatistics and Data Mining

Astrostatistics and Data Mining
  • Publisher : Springer Science & Business Media
  • File Size : 21,6 Mb
  • Release Date : 04 August 2012
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​​​​​ ​This volume provides an overview of the field of Astrostatistics understood as the sub-discipline dedicated to the statistical analysis of astronomical data. It presents examples of the application of the

Introduction to Statistical Machine Learning

Introduction to Statistical Machine Learning
  • Publisher : Morgan Kaufmann
  • File Size : 42,5 Mb
  • Release Date : 31 October 2015
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Machine learning allows computers to learn and discern patterns without actually being programmed. When Statistical techniques and machine learning are combined together they are a powerful tool for analysing various

Data Mining

Data Mining
  • Publisher : Morgan Kaufmann
  • File Size : 39,5 Mb
  • Release Date : 16 June 2024
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This book offers a thorough grounding in machine learning concepts combined with practical advice on applying machine learning tools and techniques in real-world data mining situations. Clearly written and effectively

Data Mining

Data Mining
  • Publisher : Elsevier
  • File Size : 37,7 Mb
  • Release Date : 13 July 2005
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Data Mining, Second Edition, describes data mining techniques and shows how they work. The book is a major revision of the first edition that appeared in 1999. While the basic core