Zeljko ivezic (17 resultados)
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
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Librería: Labyrinth Books, Princeton, NJ, Estados Unidos de AmericaLabyrinth Books
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EUR 59,82
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Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de AmericaPBShop.store US
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EUR 86,60
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HRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.
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Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK
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EUR 78,44
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HRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.
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Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrlandaKennys Bookshop and Art Galleries Ltd.
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EUR 81,68
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Condición: New. 2019. Revised edition. Hardcover. . . . . .
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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Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
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EUR 94,99
Envío por EUR 3,46Se envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
Condición: 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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Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books
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EUR 93,16
Envío por EUR 7,58Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Condición: New.
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Librería: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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EUR 88,75
Envío por EUR 11,00Se envía de Italia a Estados Unidos de AmericaCantidad disponible: 15 disponibles
Condición: 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
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Librería: Ria Christie Collections, Uxbridge, Reino UnidoRia Christie Collections
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EUR 91,42
Envío por EUR 13,97Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Condición: New. In.
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Librería: Kennys Bookstore, Olney, MD, Estados Unidos de AmericaKennys Bookstore
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EUR 100,21
Envío por EUR 9,10Se envía dentro de Estados Unidos de AmericaCantidad disponible: 15 disponibles
Condición: New. 2019. Revised edition. Hardcover. . . . . . Books ship from the US and Ireland.
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Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
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EUR 110,15
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Hardcover. Condición: 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 S…urvey 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
Alexander Gray, Jacob T. VanderPlas, Zeljko Ivezic, Andrew J. Connolly
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Librería: Rarewaves USA, OSWEGO, IL, Estados Unidos de AmericaRarewaves USA
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EUR 112,67
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 8 disponibles
Hardback. Condición: 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 Telesc…ope. 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
- Tapa dura
Librería: Rarewaves.com USA, London, LONDO, Reino UnidoRarewaves.com USA
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 122,20
Gastos de envío gratisSe envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 8 disponibles
Hardback. Condición: 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 Telesc…ope. 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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Librería: Russell Books, Victoria, BC, CanadaRussell Books
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EUR 132,37
Envío por EUR 17,33Se envía de Canada a Estados Unidos de AmericaCantidad disponible: 6 disponibles
Hardcover. Condición: 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
- Tapa dura
Librería: Rarewaves USA United, OSWEGO, IL, Estados Unidos de AmericaRarewaves USA United
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 114,91
Envío por EUR 43,36Se envía dentro de Estados Unidos de AmericaCantidad disponible: 8 disponibles
Hardback. Condición: 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 Telesc…ope. 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
- Tapa dura
Librería: Rarewaves.com UK, London, Reino UnidoRarewaves.com UK
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 114,64
Envío por EUR 75,81Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 8 disponibles
Hardback. Condición: 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 Telesc…ope. 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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Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 165,37
Envío por EUR 32,08Se envía de Australia a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Hardcover. Condición: 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 S…urvey 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.
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
- Tapa dura
- Impresión bajo demanda
Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 153,20
Envío por EUR 9,95Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 4 disponibles
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