Ivezic zeljko (18 risultati)

- Rilegato
Da: medimops, Berlin, Germaniamedimops
Contatta il venditoreVenditore con 5 stelleCondizione: Usato - Come nuovo
EUR 52,33
EUR 10,00 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Condizione: as new. Wie neu/Like new.

Statistics, Data Mining, and Machine Learning in Astronomy: A Practical Python Guide for the Analysis of Survey Data (Princeton Series in Modern Observational Astronomy (1))
Ivezic, Zeljko, Connolly, Andrew J., VanderPlas, Jacob T, Gray, Alexander
- Rilegato
Da: Labyrinth Books, Princeton, NJ, U.S.A.Labyrinth Books
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 60,31
EUR 3,93 spedizioneSpedito in U.S.A.Quantità: 11 disponibili
Condizione: New.

- Rilegato
Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 86,90
Spedizione gratuitaSpedito in U.S.A.Quantità: 15 disponibili
HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

- Rilegato
Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 78,50
EUR 8,91 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 15 disponibili
HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

- Rilegato
Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrlandaKennys Bookshop and Art Galleries Ltd.
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 81,68
EUR 10,50 spedizioneSpedito da Irlanda a U.S.A.Quantità: Più di 20 disponibili
Condizione: New. 2019. Revised edition. Hardcover. . . . . .

- Rilegato
Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 82,34
EUR 11,00 spedizioneSpedito da Italia a U.S.A.Quantità: Più di 20 disponibili
Condizione: new.

Statistics, Data Mining, and Machine Learning in Astronomy: A Practical Python Guide for the Analysis of Survey Data, Updated Edition (Princeton Series in Modern Observational Astronomy)
Ivezić, Željko; Connolly, Andrew J.; VanderPlas, Jacob T.; Gray, Alexander
- Rilegato
Da: Books Puddle, New York, NY, U.S.A.Books Puddle
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 97,91
EUR 3,49 spedizioneSpedito in U.S.A.Quantità: 1 disponibili
Condizione: New. Revised edition NO-PA16APR2015-KAP.

Statistics, Data Mining, and Machine Learning in Astronomy: A Practical Python Guide for the Analysis of Survey Data, Updated Edition (Princeton Series in Modern Observational Astronomy)
Ivezić, Željko; Connolly, Andrew J.; VanderPlas, Jacob T.; Gray, Alexander
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Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 91,50
EUR 13,98 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 2 disponibili
Condizione: New. In.

Statistics, Data Mining, and Machine Learning in Astronomy: A Practical Python Guide for the Analysis of Survey Data, Updated Edition (Princeton Series in Modern Observational Astronomy)
Ivezić, Željko; Connolly, Andrew J.; VanderPlas, Jacob T.; Gray, Alexander
- Rilegato
Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 97,43
EUR 7,59 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Condizione: New.

- Rilegato
Da: Kennys Bookstore, Olney, MD, U.S.A.Kennys Bookstore
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 100,79
EUR 9,18 spedizioneSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: New. 2019. Revised edition. Hardcover. . . . . . Books ship from the US and Ireland.

- Rilegato
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 111,04
Spedizione gratuitaSpedito in U.S.A.Quantità: 1 disponibili
Hardcover. Condizione: new. Hardcover. 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 Telescope and Rapid Response System, the Dark Energy Survey, and the Large Synoptic…Survey Telescope. Now fully updated, it presents a wealth of practical analysis problems, evaluates the techniques for solving them, and explains how to use various approaches for different types and sizes of data sets. Python code and sample data sets are provided for all applications described in the book. The supporting data sets have been carefully selected from contemporary astronomical surveys 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, engage with the different methods, and adapt them to their own fields of interest.An accessible textbook for students and an indispensable reference for researchers, this updated edition features new sections on deep learning methods, hierarchical Bayes modeling, and approximate Bayesian computation. The chapters have been revised throughout and the astroML code has been brought completely up to date.Fully revised and expandedDescribes the most useful statistical and data-mining methods for extracting knowledge from huge and complex astronomical data setsFeatures real-world data sets from astronomical surveysUses a freely available Python codebase throughoutIdeal for graduate students, advanced undergraduates, and working astronomers 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 Telescope and Rapid Response System, the Dark Energy Survey, and the Large Synoptic Survey Telescope. Now fully updated, it presents a wealth o Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Statistics, Data Mining, and Machine Learning in Astronomy: A Practical Python Guide for the Analysis of Survey Data, Updated Edition (Princeton Series in Modern Observational Astronomy)
Ivezić, Željko; Connolly, Andrew J.; VanderPlas, Jacob T.; Gray, Alexander
- Rilegato
Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 99,82
EUR 9,95 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Condizione: New.

Statistics, Data Mining, and Machine Learning in Astronomy
Alexander Gray, Jacob T. VanderPlas, Zeljko Ivezic, Andrew J. Connolly
- Rilegato
Da: Rarewaves USA, OSWEGO, IL, U.S.A.Rarewaves USA
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 113,59
Spedizione gratuitaSpedito in U.S.A.Quantità: 15 disponibili
Hardback. Condizione: New. 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 Telescope and Rapid Response System, the Dark Energy Survey, and the Large Synoptic Survey Teles…cope. Now fully updated, it presents a wealth of practical analysis problems, evaluates the techniques for solving them, and explains how to use various approaches for different types and sizes of data sets. Python code and sample data sets are provided for all applications described in the book. The supporting data sets have been carefully selected from contemporary astronomical surveys 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, engage with the different methods, and adapt them to their own fields of interest.An accessible textbook for students and an indispensable reference for researchers, this updated edition features new sections on deep learning methods, hierarchical Bayes modeling, and approximate Bayesian computation. The chapters have been revised throughout and the astroML code has been brought completely up to date.Fully revised and expandedDescribes the most useful statistical and data-mining methods for extracting knowledge from huge and complex astronomical data setsFeatures real-world data sets from astronomical surveysUses a freely available Python codebase throughoutIdeal for graduate students, advanced undergraduates, and working astronomers.

Statistics, Data Mining, and Machine Learning in Astronomy
Alexander Gray, Jacob T. VanderPlas, Zeljko Ivezic, Andrew J. Connolly
- Rilegato
Da: Rarewaves.com USA, London, LONDO, Regno UnitoRarewaves.com USA
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 122,43
Spedizione gratuitaSpedito da Regno Unito a U.S.A.Quantità: 11 disponibili
Hardback. Condizione: New. 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 Telescope and Rapid Response System, the Dark Energy Survey, and the Large Synoptic Survey Teles…cope. Now fully updated, it presents a wealth of practical analysis problems, evaluates the techniques for solving them, and explains how to use various approaches for different types and sizes of data sets. Python code and sample data sets are provided for all applications described in the book. The supporting data sets have been carefully selected from contemporary astronomical surveys 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, engage with the different methods, and adapt them to their own fields of interest.An accessible textbook for students and an indispensable reference for researchers, this updated edition features new sections on deep learning methods, hierarchical Bayes modeling, and approximate Bayesian computation. The chapters have been revised throughout and the astroML code has been brought completely up to date.Fully revised and expandedDescribes the most useful statistical and data-mining methods for extracting knowledge from huge and complex astronomical data setsFeatures real-world data sets from astronomical surveysUses a freely available Python codebase throughoutIdeal for graduate students, advanced undergraduates, and working astronomers.

- Rilegato
Da: Russell Books, Victoria, BC, CanadaRussell Books
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 133,44
EUR 17,47 spedizioneSpedito da Canada a U.S.A.Quantità: 6 disponibili
Hardcover. Condizione: New. Special order direct from the distributor.

Statistics, Data Mining, and Machine Learning in Astronomy
Alexander Gray, Jacob T. VanderPlas, Zeljko Ivezic, Andrew J. Connolly
- Rilegato
Da: Rarewaves USA United, OSWEGO, IL, U.S.A.Rarewaves USA United
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 115,72
EUR 43,71 spedizioneSpedito in U.S.A.Quantità: 15 disponibili
Hardback. Condizione: New. 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 Telescope and Rapid Response System, the Dark Energy Survey, and the Large Synoptic Survey Teles…cope. Now fully updated, it presents a wealth of practical analysis problems, evaluates the techniques for solving them, and explains how to use various approaches for different types and sizes of data sets. Python code and sample data sets are provided for all applications described in the book. The supporting data sets have been carefully selected from contemporary astronomical surveys 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, engage with the different methods, and adapt them to their own fields of interest.An accessible textbook for students and an indispensable reference for researchers, this updated edition features new sections on deep learning methods, hierarchical Bayes modeling, and approximate Bayesian computation. The chapters have been revised throughout and the astroML code has been brought completely up to date.Fully revised and expandedDescribes the most useful statistical and data-mining methods for extracting knowledge from huge and complex astronomical data setsFeatures real-world data sets from astronomical surveysUses a freely available Python codebase throughoutIdeal for graduate students, advanced undergraduates, and working astronomers.

Statistics, Data Mining, and Machine Learning in Astronomy
Alexander Gray, Jacob T. VanderPlas, Zeljko Ivezic, Andrew J. Connolly
- Rilegato
Da: Rarewaves.com UK, London, Regno UnitoRarewaves.com UK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 114,74
EUR 75,88 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 11 disponibili
Hardback. Condizione: New. 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 Telescope and Rapid Response System, the Dark Energy Survey, and the Large Synoptic Survey Teles…cope. Now fully updated, it presents a wealth of practical analysis problems, evaluates the techniques for solving them, and explains how to use various approaches for different types and sizes of data sets. Python code and sample data sets are provided for all applications described in the book. The supporting data sets have been carefully selected from contemporary astronomical surveys 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, engage with the different methods, and adapt them to their own fields of interest.An accessible textbook for students and an indispensable reference for researchers, this updated edition features new sections on deep learning methods, hierarchical Bayes modeling, and approximate Bayesian computation. The chapters have been revised throughout and the astroML code has been brought completely up to date.Fully revised and expandedDescribes the most useful statistical and data-mining methods for extracting knowledge from huge and complex astronomical data setsFeatures real-world data sets from astronomical surveysUses a freely available Python codebase throughoutIdeal for graduate students, advanced undergraduates, and working astronomers.

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Da: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 164,16
EUR 32,34 spedizioneSpedito da Australia a U.S.A.Quantità: 1 disponibili
Hardcover. Condizione: new. Hardcover. 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 Telescope and Rapid Response System, the Dark Energy Survey, and the Large Synoptic…Survey Telescope. Now fully updated, it presents a wealth of practical analysis problems, evaluates the techniques for solving them, and explains how to use various approaches for different types and sizes of data sets. Python code and sample data sets are provided for all applications described in the book. The supporting data sets have been carefully selected from contemporary astronomical surveys 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, engage with the different methods, and adapt them to their own fields of interest.An accessible textbook for students and an indispensable reference for researchers, this updated edition features new sections on deep learning methods, hierarchical Bayes modeling, and approximate Bayesian computation. The chapters have been revised throughout and the astroML code has been brought completely up to date.Fully revised and expandedDescribes the most useful statistical and data-mining methods for extracting knowledge from huge and complex astronomical data setsFeatures real-world data sets from astronomical surveysUses a freely available Python codebase throughoutIdeal for graduate students, advanced undergraduates, and working astronomers 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 Telescope and Rapid Response System, the Dark Energy Survey, and the Large Synoptic Survey Telescope. Now fully updated, it presents a wealth o Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.