Kumar nirman (42 resultados)
Random Number Generators for Computer Simulation and Cyber Security: Design, Search, Theory, and Application (Synthesis Lectures on Mathematics & Statistics)
Deng, Lih-Yuan; Kumar, Nirman; Lu, Henry Horng-Shing; Yang, Ching-Chi
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Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books
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EUR 55,91
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Random Number Generators for Computer Simulation and Cyber Security: Design, Search, Theory, and Application (Synthesis Lectures on Mathematics & Statistics)
Deng, Lih-Yuan; Kumar, Nirman; Lu, Henry Horng-Shing; Yang, Ching-Chi
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Librería: Ria Christie Collections, Uxbridge, Reino UnidoRia Christie Collections
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EUR 48,79
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Dimensionality Reduction in Data Science
Garzon, Max (EDT); Yang, Ching-chi (EDT); Venugopal, Deepak (EDT); Kumar, Nirman (EDT); Jana, Kalidas (EDT)
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
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EUR 61,13
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Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de AmericaPBShop.store US
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EUR 63,52
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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 59,26
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HRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.
Dimensionality Reduction in Data Science
Garzon, Max (EDT); Yang, Ching-chi (EDT); Venugopal, Deepak (EDT); Kumar, Nirman (EDT); Jana, Kalidas (EDT)
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
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EUR 65,04
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Condición: As New. Unread book in perfect condition.
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Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
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EUR 70,82
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Hardcover. Condición: new. Hardcover. This book provides a practical and fairly comprehensive review of Data Science through the lens of dimensionality reduction, as well as hands-on techniques to tackle problems with data collected in the real world. State-of-the-art results and solutions from statistics, computer science and m…athematics are explained from the point of view of a practitioner in any domain science, such as biology, cyber security, chemistry, sports science and many others. Quantitative and qualitative assessment methods are described to implement and validate the solutions back in the real world where the problems originated.The ability to generate, gather and store volumes of data in the order of tera- and exo bytes daily has far outpaced our ability to derive useful information with available computational resources for many domains.This book focuses on data science and problem definition, data cleansing, feature selection and extraction,statistical, geometric, information-theoretic, biomolecular and machine learning methods for dimensionality reduction of big datasets and problem solving, as well as a comparative assessment of solutions in a real-world setting.This book targets professionals working within related fields with an undergraduate degree in any science area, particularly quantitative. Readers should be able to follow examples in this book that introduce each method or technique. These motivating examples are followed by precise definitions of the technical concepts required and presentation of the results in general situations. These concepts require a degree of abstraction that can be followed by re-interpreting concepts like in the original example(s). Finally, each section closes with solutions to the original problem(s) afforded by these techniques, perhaps in various ways to compare and contrast dis/advantages to other solutions. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Más imágenesDimensionality Reduction in Data Science
Deepak Venugopal, Nirman Kumar, Ching-chi Yang, Max Garzon, Kalidas Jana
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Librería: Rarewaves.com USA, London, LONDO, Reino UnidoRarewaves.com USA
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EUR 72,95
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Hardback. Condición: New. 2022 ed. This book provides a practical and fairly comprehensive review of Data Science through the lens of dimensionality reduction, as well as hands-on techniques to tackle problems with data collected in the real world. State-of-the-art results and solutions from statistics, computer science and math…ematics are explained from the point of view of a practitioner in any domain science, such as biology, cyber security, chemistry, sports science and many others. Quantitative and qualitative assessment methods are described to implement and validate the solutions back in the real world where the problems originated.The ability to generate, gather and store volumes of data in the order of tera- and exo bytes daily has far outpaced our ability to derive useful information with available computational resources for many domains.This book focuses on data science and problem definition, data cleansing, feature selection and extraction,statistical, geometric, information-theoretic, biomolecular and machine learning methods for dimensionality reduction of big datasets and problem solving, as well as a comparative assessment of solutions in a real-world setting.This book targets professionals working within related fields with an undergraduate degree in any science area, particularly quantitative. Readers should be able to follow examples in this book that introduce each method or technique. These motivating examples are followed by precise definitions of the technical concepts required and presentation of the results in general situations. These concepts require a degree of abstraction that can be followed by re-interpreting concepts like in the original example(s). Finally, each section closes with solutions to the original problem(s) afforded by these techniques, perhaps in various ways to compare and contrast dis/advantages to other solutions.
Dimensionality Reduction in Data Science
Garzon, Max (EDT); Yang, Ching-chi (EDT); Venugopal, Deepak (EDT); Kumar, Nirman (EDT); Jana, Kalidas (EDT)
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Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
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EUR 59,25
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Dimensionality Reduction in Data Science
Max Garzon, Ching-Chi Yang, Deepak Venugopal, Nirman Kumar, Kalidas Jana, Lih-Yuan Deng
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Librería: Chiron Media, Wallingford, Reino UnidoChiron Media
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EUR 59,26
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Hardcover. Condición: New.
Random Number Generators for Computer Simulation and Cyber Security: Design, Search, Theory, and Application (Synthesis Lectures on Mathematics & Statistics)
Deng, Lih-Yuan; Kumar, Nirman; Lu, Henry Horng-Shing; Yang, Ching-Chi
- Tapa dura
Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
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EUR 74,45
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Condición: New.
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Librería: Ria Christie Collections, Uxbridge, Reino UnidoRia Christie Collections
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EUR 64,95
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Condición: New. In.
Dimensionality Reduction in Data Science
Garzon, Max (EDT); Yang, Ching-chi (EDT); Venugopal, Deepak (EDT); Kumar, Nirman (EDT); Jana, Kalidas (EDT)
- Tapa dura
Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
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EUR 66,89
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Condición: As New. Unread book in perfect condition.
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Librería: Ria Christie Collections, Uxbridge, Reino UnidoRia Christie Collections
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EUR 73,41
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Condición: New. In.
Random Number Generators for Computer Simulation and Cyber Security: Design, Search, Theory, and Application
Deng, Lih-yuan/ Kumar, Nirman/ Lu, Henry Horng-Shing/ Yang, Ching-chi
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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EUR 75,46
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Hardcover. Condición: Brand New. 250 pages. 9.45x6.62x9.61 inches. In Stock.
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Librería: Speedyhen, Hertfordshire, Reino UnidoSpeedyhen
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EUR 53,88
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Dimensionality Reduction in Data Science
Garzon, Max (Editor) / Yang, Ching-Chi (Editor) / Venugopal, Deepak (Editor) / Kumar, Nirman (Editor) / Jana, Kalidas (Editor) / Deng, Lih-Yuan (Editor)
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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EUR 93,01
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Paperback. Condición: Brand New. 276 pages. 9.25x6.10x0.67 inches. In Stock.
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Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
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EUR 102,92
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Condición: New.
Idioma: Inglés
Editorial: Springer, Berlin|Springer International Publishing|Springer, 2023
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Librería: moluna, Greven, Alemaniamoluna
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EUR 55,78
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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Hardcover. Condición: Brand New. 276 pages. 9.25x6.10x0.69 inches. In Stock.
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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EUR 50,28
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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a practical and fairly comprehensive review of Data Science through the lensof dimensionality reduction, as well as hands-on techniques to tackle problems with data collected in the real world. State-of-the-art results and soluti…ons from statistics, computer science and mathematics are explained from the point of view of a practitioner in any domain science, such as biology, cyber security, chemistry, sports science and many others. Quantitative and qualitative assessment methods are described to implement and validate the solutions back in the real world where the problems originated.The ability to generate, gather and store volumes of data in the order of tera- and exo bytes daily has far outpaced our ability to derive useful information with available computational resources for many domains.This book focuses on data science and problem definition, data cleansing, feature selection and extraction,statistical, geometric, information-theoretic, biomolecular and machine learning methods for dimensionality reduction of big datasets and problem solving, as well as a comparative assessment of solutions in a real-world setting.This book targets professionals working within related fields with an undergraduate degree in any science area, particularly quantitative. Readers should be able to follow examples in this book that introduce each method or technique. These motivating examples are followed by precise definitions of the technical concepts required and presentation of the results in general situations. These concepts require a degree of abstraction that can be followed by re-interpreting concepts like in the original example(s). Finally, each section closes with solutions to the original problem(s) afforded by these techniques, perhaps in various ways to compare and contrast dis/advantages toother solutions.
Idioma: Inglés
Editorial: Springer, Berlin|Springer International Publishing|Springer, 2022
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Librería: moluna, Greven, Alemaniamoluna
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EUR 67,49
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Librería: preigu, Osnabrück, Alemaniapreigu
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EUR 47,70
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Taschenbuch. Condición: Neu. Dimensionality Reduction in Data Science | Max Garzon (u. a.) | Taschenbuch | xi | Englisch | 2023 | Springer | EAN 9783031053733 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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EUR 69,54
Envío por EUR 62,94Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a practical and fairly comprehensive review of Data Science through the lensof dimensionality reduction, as well as hands-on techniques to tackle problems with data collected in the real world. State-of-the-art results and solutions fro…m statistics, computer science and mathematics are explained from the point of view of a practitioner in any domain science, such as biology, cyber security, chemistry, sports science and many others. Quantitative and qualitative assessment methods are described to implement and validate the solutions back in the real world where the problems originated.The ability to generate, gather and store volumes of data in the order of tera- and exo bytes daily has far outpaced our ability to derive useful information with available computational resources for many domains.This book focuses on data science and problem definition, data cleansing, feature selection and extraction,statistical, geometric, information-theoretic, biomolecular and machine learning methods for dimensionality reduction of big datasets and problem solving, as well as a comparative assessment of solutions in a real-world setting.This book targets professionals working within related fields with an undergraduate degree in any science area, particularly quantitative. Readers should be able to follow examples in this book that introduce each method or technique. These motivating examples are followed by precise definitions of the technical concepts required and presentation of the results in general situations. These concepts require a degree of abstraction that can be followed by re-interpreting concepts like in the original example(s). Finally, each section closes with solutions to the original problem(s) afforded by these techniques, perhaps in various ways to compare and contrast dis/advantages toother solutions.
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Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
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EUR 105,85
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Hardcover. Condición: new. Hardcover. This book provides a practical and fairly comprehensive review of Data Science through the lens of dimensionality reduction, as well as hands-on techniques to tackle problems with data collected in the real world. State-of-the-art results and solutions from statistics, computer science and m…athematics are explained from the point of view of a practitioner in any domain science, such as biology, cyber security, chemistry, sports science and many others. Quantitative and qualitative assessment methods are described to implement and validate the solutions back in the real world where the problems originated.The ability to generate, gather and store volumes of data in the order of tera- and exo bytes daily has far outpaced our ability to derive useful information with available computational resources for many domains.This book focuses on data science and problem definition, data cleansing, feature selection and extraction,statistical, geometric, information-theoretic, biomolecular and machine learning methods for dimensionality reduction of big datasets and problem solving, as well as a comparative assessment of solutions in a real-world setting.This book targets professionals working within related fields with an undergraduate degree in any science area, particularly quantitative. Readers should be able to follow examples in this book that introduce each method or technique. These motivating examples are followed by precise definitions of the technical concepts required and presentation of the results in general situations. These concepts require a degree of abstraction that can be followed by re-interpreting concepts like in the original example(s). Finally, each section closes with solutions to the original problem(s) afforded by these techniques, perhaps in various ways to compare and contrast dis/advantages to other solutions. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Dimensionality Reduction in Data Science
Deepak Venugopal, Nirman Kumar, Ching-chi Yang, Max Garzon, Kalidas Jana
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Librería: Rarewaves.com UK, London, Reino UnidoRarewaves.com UK
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EUR 67,70
Envío por EUR 75,90Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Hardback. Condición: New. 2022 ed. This book provides a practical and fairly comprehensive review of Data Science through the lens of dimensionality reduction, as well as hands-on techniques to tackle problems with data collected in the real world. State-of-the-art results and solutions from statistics, computer science and math…ematics are explained from the point of view of a practitioner in any domain science, such as biology, cyber security, chemistry, sports science and many others. Quantitative and qualitative assessment methods are described to implement and validate the solutions back in the real world where the problems originated.The ability to generate, gather and store volumes of data in the order of tera- and exo bytes daily has far outpaced our ability to derive useful information with available computational resources for many domains.This book focuses on data science and problem definition, data cleansing, feature selection and extraction,statistical, geometric, information-theoretic, biomolecular and machine learning methods for dimensionality reduction of big datasets and problem solving, as well as a comparative assessment of solutions in a real-world setting.This book targets professionals working within related fields with an undergraduate degree in any science area, particularly quantitative. Readers should be able to follow examples in this book that introduce each method or technique. These motivating examples are followed by precise definitions of the technical concepts required and presentation of the results in general situations. These concepts require a degree of abstraction that can be followed by re-interpreting concepts like in the original example(s). Finally, each section closes with solutions to the original problem(s) afforded by these techniques, perhaps in various ways to compare and contrast dis/advantages to other solutions.
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Librería: Buchpark, Trebbin, AlemaniaBuchpark
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EUR 53,72
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Condición: Hervorragend. Zustand: Hervorragend | Seiten: 280 | Sprache: Englisch | Produktart: Bücher | This book provides a practical and fairly comprehensive review of Data Science through the lens of dimensionality reduction, as well as hands-on techniques to tackle problems with data collected in the real world. State-of-the…-art results and solutions from statistics, computer science and mathematics are explained from the point of view of a practitioner in any domain science, such as biology, cyber security, chemistry, sports science and many others. Quantitative and qualitative assessment methods are described to implement and validate the solutions back in the real world where the problems originated.The ability to generate, gather and store volumes of data in the order of tera- and exo bytes daily has far outpaced our ability to derive useful information with available computational resources for many domains.This book focuses on data science and problem definition, data cleansing, feature selection and extraction,statistical, geometric, information-theoretic, biomolecular and machine learning methods for dimensionality reduction of big datasets and problem solving, as well as a comparative assessment of solutions in a real-world setting.This book targets professionals working within related fields with an undergraduate degree in any science area, particularly quantitative. Readers should be able to follow examples in this book that introduce each method or technique. These motivating examples are followed by precise definitions of the technical concepts required and presentation of the results in general situations. These concepts require a degree of abstraction that can be followed by re-interpreting concepts like in the original example(s). Finally, each section closes with solutions to the original problem(s) afforded by these techniques, perhaps in various ways to compare and contrast dis/advantages to other solutions.
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Librería: BUCHSERVICE / ANTIQUARIAT Lars Lutzer, Wahlstedt, AlemaniaBUCHSERVICE / ANTIQUARIAT Lars Lutzer
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EUR 189,90
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Hardcover. Condición: gut. 2022. Dimensionality Reduction in Data Science In deutscher Sprache. pages.
Random Number Generators for Computer Simulation and Cyber Security: Design, Search, Theory, and Application
Deng, Lih-yuan/ Kumar, Nirman/ Lu, Henry Horng-Shing/ Yang, Ching-chi
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- Impresión bajo demanda
Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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EUR 42,08
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Hardcover. Condición: Brand New. 250 pages. 9.45x6.62x9.61 inches. In Stock. This item is printed on demand.
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Librería: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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EUR 54,23
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Condición: new. Questo è un articolo print on demand.
