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Publicado por Springer International Publishing AG, Cham, 2022
ISBN 10: 3031053702 ISBN 13: 9783031053702
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Añadir al carritoHardcover. 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 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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Publicado por Springer International Publishing AG, 2022
ISBN 10: 3031053702 ISBN 13: 9783031053702
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Añadir al carritoHRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.
Publicado por Springer, 2012
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Añadir al carritopaperback. Condición: Good. Ex-library copy with stamps and stickers. The pages are lightly tanned. The copy shows minor external wear, but is in otherwise clean condition.
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Añadir al carritohardcover. Condición: Sehr gut. 286 p. In very good condition. ISBN: 9783540561491 Sprache: Englisch Gewicht in Gramm: 549.
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Publicado por Springer International Publishing AG, CH, 2022
ISBN 10: 3031053702 ISBN 13: 9783031053702
Librería: Rarewaves.com USA, London, LONDO, Reino Unido
EUR 71,45
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Añadir al carritoHardback. 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 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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Añadir al carritoCondición: New. pp. 292.
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Añadir al carritoPaperback. Condición: Brand New. reprint edition. 286 pages. 9.25x6.10x0.66 inches. In Stock.
Idioma: Inglés
Publicado por Springer-Verlag New York Inc, 2008
ISBN 10: 3540779612 ISBN 13: 9783540779612
Librería: Revaluation Books, Exeter, Reino Unido
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Añadir al carritoPaperback. Condición: Brand New. 1st edition. 292 pages. 9.25x6.25x0.75 inches. In Stock.
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Publicado por Springer Berlin Heidelberg, 2012
ISBN 10: 3642779077 ISBN 13: 9783642779077
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Publicado por Springer, Berlin|Springer International Publishing|Springer, 2023
ISBN 10: 3031053737 ISBN 13: 9783031053733
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Añadir al carritoHardcover. Condición: Brand New. 276 pages. 9.25x6.10x0.69 inches. In Stock.
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Publicado por Springer International Publishing, 2023
ISBN 10: 3031053737 ISBN 13: 9783031053733
Librería: AHA-BUCH GmbH, Einbeck, Alemania
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Añadir al carritoTaschenbuch. 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 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.