Dimensionality Reduction in Data Science

Lingua: inglese

Editore: Springer, 2022

3031053702 / 9783031053702

Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

Venditore con 5 stelle

Venditore AbeBooks dal 14 agosto 2006

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Condizione: Nuovo

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Spedito da Germania a U.S.A.

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Descrizione dell’articolo da parte del venditore

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. …

Codice articolo 9783031053702

Titolo
Dimensionality Reduction in Data Science
Autore
Deepak Venugopal
Editore
Springer
Anno di pubblicazione
2022
Condizione
Neu
Rilegatura
Buch
Lingua
inglese
ISBN 10
3031053702
ISBN 13
9783031053702
Peso dell'articolo
588 grammi
Dimensioni
241x160x21 mm

AHA-BUCH GmbH

Einbeck, Germania

Venditore con 5 stelle

Venditore AbeBooks dal 14 agosto 2006

Tariffe di spedizione da Germania a U.S.A.

ArticoloDa 7 a 10 giorni lavorativiDa 5 a 7 giorni lavorativi
Primo articoloEUR 35,00EUR 45,00
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