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Random Number Generators for Computer Simulation and Cyber Security: Design, Search, Theory, and Application (Synthesis Lectures on Mathematics & Statistics)
Vendeur : Books From California, Simi Valley, CA, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
EUR 24,36
EUR 4,25 shipping
Expédition nationale : Etats-UnisQuantité disponible : 1 disponible(s)
Ajouter au panierhardcover. Etat : Very Good.
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Random Number Generators for Computer Simulation and Cyber Security: Design, Search, Theory, and Application
Vendeur : Books Puddle, New York, NY, Etats-Unis
Évaluation du vendeur 4 sur 5 étoiles
EUR 41,82
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Expédition nationale : Etats-UnisQuantité disponible : 1 disponible(s)
Ajouter au panierEtat : New.
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Random Number Generators for Computer Simulation and Cyber Security: Design, Search, Theory, and Application
Vendeur : Majestic Books, Hounslow, Royaume-Uni
Évaluation du vendeur 4 sur 5 étoiles
EUR 39,17
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Expédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : 1 disponible(s)
Ajouter au panierEtat : New.
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Random Number Generators for Computer Simulation and Cyber Security: Design, Search, Theory, and Application (Synthesis Lectures on Mathematics & Statistics)
Vendeur : California Books, Miami, FL, Etats-Unis
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EUR 49,17
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Random Number Generators for Computer Simulation and Cyber Security: Design, Search, Theory, and Application
Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
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EUR 41,04
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Random Number Generators for Computer Simulation and Cyber Security: Design, Search, Theory, and Application (Synthesis Lectures on Mathematics & Statistics)
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
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EUR 46,48
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Dimensionality Reduction in Data Science
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
EUR 58,63
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Dimensionality Reduction in Data Science (Hardcover)
Langue: anglais
Edité par Springer International Publishing AG, Cham, 2022
ISBN 10 : 3031053702 ISBN 13 : 9783031053702
Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
EUR 60,96
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Expédition nationale : Etats-UnisQuantité disponible : 1 disponible(s)
Ajouter au panierHardcover. Etat : 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 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Dimensionality Reduction in Data Science
Langue: anglais
Edité par Springer International Publishing AG, 2022
ISBN 10 : 3031053702 ISBN 13 : 9783031053702
Vendeur : PBShop.store US, Wood Dale, IL, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
EUR 61,15
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Ajouter au panierHRD. Etat : New. New Book. Shipped from UK. Established seller since 2000.
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Dimensionality Reduction in Data Science
Langue: anglais
Edité par Springer International Publishing AG, 2022
ISBN 10 : 3031053702 ISBN 13 : 9783031053702
Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
EUR 57,44
EUR 5,76 shipping
Expédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : 1 disponible(s)
Ajouter au panierHRD. Etat : New. New Book. Shipped from UK. Established seller since 2000.
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Dimensionality Reduction in Data Science
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
EUR 63,61
EUR 2,25 shipping
Expédition nationale : Etats-UnisQuantité disponible : Plus de 20 disponibles
Ajouter au panierEtat : As New. Unread book in perfect condition.
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Dimensionality Reduction in Data Science
Vendeur : California Books, Miami, FL, Etats-Unis
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EUR 69,37
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Dimensionality Reduction in Data Science
Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
EUR 65,91
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Dimensionality Reduction in Data Science
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
EUR 57,43
EUR 17,22 shipping
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Ajouter au panierEtat : New.
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Dimensionality Reduction in Data Science
Vendeur : California Books, Miami, FL, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
EUR 74,64
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Dimensionality Reduction in Data Science
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
EUR 62,01
EUR 13,76 shipping
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Ajouter au panierEtat : New. In.
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Dimensionality Reduction in Data Science
Langue: anglais
Edité par Springer International Publishing AG, CH, 2022
ISBN 10 : 3031053702 ISBN 13 : 9783031053702
Vendeur : Rarewaves.com USA, London, LONDO, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
EUR 78,57
Livraison gratuite
Expédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : 1 disponible(s)
Ajouter au panierHardback. Etat : 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 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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Random Number Generators for Computer Simulation and Cyber Security: Design, Search, Theory, and Application
Vendeur : Revaluation Books, Exeter, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
EUR 67,13
EUR 14,35 shipping
Expédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : 2 disponible(s)
Ajouter au panierHardcover. Etat : Brand New. 250 pages. 9.45x6.62x9.61 inches. In Stock.
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Dimensionality Reduction in Data Science
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
EUR 65,73
EUR 17,22 shipping
Expédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : Plus de 20 disponibles
Ajouter au panierEtat : As New. Unread book in perfect condition.
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Dimensionality Reduction in Data Science
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
EUR 70,14
EUR 13,76 shipping
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Ajouter au panierEtat : New. In.
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Dimensionality Reduction in Data Science
Vendeur : Books Puddle, New York, NY, Etats-Unis
Évaluation du vendeur 4 sur 5 étoiles
EUR 88,02
EUR 3,40 shipping
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Ajouter au panierEtat : New. pp. 280.
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Dimensionality Reduction in Data Science
Vendeur : Books Puddle, New York, NY, Etats-Unis
Évaluation du vendeur 4 sur 5 étoiles
EUR 93,34
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EUR 53,06
EUR 47,08 shipping
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Dimensionality Reduction in Data Science
Langue: anglais
Edité par Springer, Berlin|Springer International Publishing|Springer, 2023
ISBN 10 : 3031053737 ISBN 13 : 9783031053733
EUR 50,48
EUR 48,99 shipping
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Dimensionality Reduction in Data Science
Vendeur : Revaluation Books, Exeter, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
EUR 90,94
EUR 11,48 shipping
Expédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : 2 disponible(s)
Ajouter au panierPaperback. Etat : Brand New. 276 pages. 9.25x6.10x0.67 inches. In Stock.
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Dimensionality Reduction in Data Science
Vendeur : Revaluation Books, Exeter, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
EUR 99,57
EUR 14,35 shipping
Expédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : 2 disponible(s)
Ajouter au panierHardcover. Etat : Brand New. 276 pages. 9.25x6.10x0.69 inches. In Stock.
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Dimensionality Reduction in Data Science
Langue: anglais
Edité par Springer International Publishing, 2023
ISBN 10 : 3031053737 ISBN 13 : 9783031053733
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
EUR 50,28
EUR 62,15 shipping
Expédition depuis Allemagne vers Etats-UnisQuantité disponible : 1 disponible(s)
Ajouter au panierTaschenbuch. Etat : 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 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.
-
Dimensionality Reduction in Data Science
Langue: anglais
Edité par Springer, Berlin|Springer International Publishing|Springer, 2022
ISBN 10 : 3031053702 ISBN 13 : 9783031053702
EUR 67,49
EUR 48,99 shipping
Expédition depuis Allemagne vers Etats-UnisQuantité disponible : 1 disponible(s)
Ajouter au panierEtat : New.
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Dimensionality Reduction in Data Science (Hardcover)
Langue: anglais
Edité par Springer International Publishing AG, Cham, 2022
ISBN 10 : 3031053702 ISBN 13 : 9783031053702
Vendeur : AussieBookSeller, Truganina, VIC, Australie
Évaluation du vendeur 5 sur 5 étoiles
EUR 102,29
EUR 31,54 shipping
Expédition depuis Australie vers Etats-UnisQuantité disponible : 1 disponible(s)
Ajouter au panierHardcover. Etat : 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 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
-
Dimensionality Reduction in Data Science
Langue: anglais
Edité par Springer International Publishing, 2022
ISBN 10 : 3031053702 ISBN 13 : 9783031053702
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
EUR 69,54
EUR 62,94 shipping
Expédition depuis Allemagne vers Etats-UnisQuantité disponible : 1 disponible(s)
Ajouter au panierBuch. Etat : 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 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.
