Data analysis astronomy (199 résultats)

hardcover. Etat : Very Good. Interior is clean and unmarked. Decent amount of wear and scuffing on the covers. A few stray ink stains on outward facing page edges. Hardcover. LW.

hardcover. Etat : Very Good. Interior is clean and unmarked. Some wear and scuffing on exterior, including some bending in the bottom right of the front cover. A few ink stains on outward-facing page edges. Hardcover. LW.

Hardback. Etat : Very Good. 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 setsFeatures real-world data sets from contemporary astronomical surveysUses a freely available Python codebase throughoutIdeal for students and working astronomers.…

Hardback. Etat : Good. 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 setsFeatures real-world data sets from contemporary astronomical surveysUses a freely available Python codebase throughoutIdeal for students and working astronomers.…

Hardback. Etat : Very Good. 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 setsFeatures real-world data sets from contemporary astronomical surveysUses a freely available Python codebase throughoutIdeal for students and working astronomers.…

Hardback. Etat : Good. 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 setsFeatures real-world data sets from contemporary astronomical surveysUses a freely available Python codebase throughoutIdeal for students and working astronomers.…

Etat : acceptable.

hardcover. Etat : Very Good. A nice copy. Cover has minor shelf rubbings. Binding is tight. Your Satisfaction Guaranteed. We ship daily. Expedited shipping available.

Hardcover. Etat : Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.

Etat : New.

Etat : New.

Etat : As New. Unread book in perfect condition.

Etat : Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1200grams, ISBN.

Hardcover. Etat : Very Good. No Dust Jacket. First Edition. Spine toned, cocked. Photos upon request. International shipping billed at cost.; Ettore Majorana International Science Series, No. 59; Large 8vo 9" - 10" tall; 364 pages.

Etat : very_good. This is a well-cared-for used book with light signs of previous use. There may be minor cover wear, a faint crease, or slight spine wear, but overall it's in great shape and fully readable. Please note: -May contain library or rental stickers. -Supplemental materials e.g., CDs, access codes, inserts are not guaranteed. -Box sets may not include original exterior box. Your satisfaction is our top priority! If you have any questions or concerns about your order, please don't hesitate to reach out. Thank you for shopping with us and supporting small businessâ"happy reading. …

Etat : good. A copy that has been read, remains in good condition. All pages are intact, and the cover is intact. The spine and cover show signs of wear. Pages can include notes and highlighting and show signs of wear, and the copy can include "From the library of" labels or previous owner inscriptions. 100% GUARANTEE! Shipped with delivery confirmation, if you're not satisfied with purchase please return item! Ships via media mail.…

Etat : Very Good. 158 pp., Hardcover, very good. - If you are reading this, this item is actually (physically) in our stock and ready for shipment once ordered. We are not bookjackers. Buyer is responsible for any additional duties, taxes, or fees required by recipient's country.

Etat : Sehr gut. 1672 S. Vol. II published 1993 and Vol. III 1994. With tables. Sehr guter Zustand/ very good Sprache: Englisch Gewicht in Gramm: 2100 Hardcover/ Pappband fest gebunden.

Etat : As New. Unread book in perfect condition.

Etat : New.

Etat : Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1050grams, ISBN:0306431580. …

Gr.-8°, original hardcover. 1. ed. 158 p. Stamp on title, otherwise fine copy. Sprache: Englisch Gewicht in Gramm: 0.

Etat : New.

Etat : New.

Hardcover. Etat : Gut. 158 p. Ex-library with stamp and library-signature. GOOD condition, some traces of use. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. C-05354 3540979093 Sprache: Englisch Gewicht in Gramm: 550.

Etat : New.

Etat : New.

Etat : New.

Etat : New.

Etat : New.