Zeljko ivezic (18 risultati)
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, U.S.A.Labyrinth Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 59,43
EUR 3,88 spedizioneSpedito in U.S.A.Quantità: 11 disponibili
Condizione: New.
- Rilegato
Da: PBShop.store US, Wood Dale, U.S.A.PBShop.store US
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 85,64
Spedizione gratuitaSpedito in 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, 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: 15 disponibili
Condizione: New. 2019. Revised edition. Hardcover. . . . . .
- Rilegato
Da: Brook Bookstore On Demand, Napoli, ItaliaBrook Bookstore On Demand
Contatta il venditoreVenditore con 3 stelleCondizione: Nuovo
EUR 82,05
EUR 11,00 spedizioneSpedito da Italia a U.S.A.Quantità: 15 disponibili
Condizione: new.
- Rilegato
Da: Speedyhen LLC, Hialeah, U.S.A.Speedyhen LLC
Contatta il venditoreVenditore con 3 stelleCondizione: Nuovo
EUR 98,06
Spedizione gratuitaSpedito in U.S.A.Quantità: 4 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, U.S.A.Books Puddle
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 95,64
EUR 3,44 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
- Rilegato
Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 94,19
EUR 7,53 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 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: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 90,08
EUR 13,87 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 2 disponibili
Condizione: New. In.
Statistics, Data Mining, and Machine Learning in Astronomy
Alexander Gray, Jacob T. VanderPlas, Zeljko Ivezic, Andrew J. Connolly
- Rilegato
Da: Rarewaves USA, OSWEGO, U.S.A.Rarewaves USA
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 107,21
Spedizione gratuitaSpedito in U.S.A.Quantità: Più di 20 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: 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, GermaniaBiblios
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 96,17
EUR 9,95 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Condizione: New.
- Rilegato
Da: Kennys Bookstore, Olney, U.S.A.Kennys Bookstore
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 101,41
EUR 9,05 spedizioneSpedito in U.S.A.Quantità: 15 disponibili
Condizione: New. 2019. Revised edition. Hardcover. . . . . . Books ship from the US and Ireland.
Statistics, Data Mining, and Machine Learning in Astronomy
Alexander Gray, Jacob T. VanderPlas, Zeljko Ivezic, Andrew J. Connolly
- Rilegato
Da: Rarewaves.com USA, London, Regno UnitoRarewaves.com USA
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 113,69
Spedizione gratuitaSpedito da Regno Unito a U.S.A.Quantità: 8 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: Grand Eagle Retail, Bensenville, U.S.A.Grand Eagle Retail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 119,62
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.
- Rilegato
Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 94,19
EUR 42,84 spedizioneSpedito da Regno Unito 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 UK warehouse or from our Australian or US warehouses, depending on stock availability.
- Rilegato
Da: Russell Books, Victoria, CanadaRussell Books
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 125,18
EUR 17,22 spedizioneSpedito da Canada a U.S.A.Quantità: 6 disponibili
Hardcover. Condizione: New. Revised. 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, U.S.A.Rarewaves USA United
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 110,05
EUR 43,07 spedizioneSpedito in U.S.A.Quantità: Più di 20 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 107,24
EUR 75,25 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 8 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: AussieBookSeller, Truganina, AustraliaAussieBookSeller
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 166,71
EUR 31,87 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.
