9783030433833 - data science and productivity analytics: 290 (international series in operations research & management science, 290) de charles (11 resultados)
Idioma: Inglés
Editorial: Springer 2020
Serie: International Series in Operations Research & Management Science, Libro 280 de 323. Libro 280 de 323 - International Series in Operations Research & Management Science
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Librería: Ria Christie Collections, Uxbridge, Reino UnidoRia Christie Collections
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Serie: International Series in Operations Research & Management Science, Libro 280 de 323. Libro 280 de 323 - International Series in Operations Research & Management Science
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Serie: International Series in Operations Research & Management Science, Libro 280 de 323. Libro 280 de 323 - International Series in Operations Research & Management Science
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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book includes a spectrum of concepts, such as performance, productivity, operations research, econometrics, and data science, for the practically and theoretically important areas of 'productivity analysis/data envelopment analysis' and 'data science…/big data'. Data science is defined as the collection of scientific methods, processes, and systems dedicated to extracting knowledge or insights from data and it develops on concepts from various domains, containing mathematics and statistical methods, operations research, machine learning, computer programming, pattern recognition, and data visualisation, among others.Examples of data science techniques include linear and logistic regressions, decision trees, Naïve Bayesian classifier, principal component analysis, neural networks, predictive modelling, deep learning, text analysis, survival analysis, and so on, all of which allow using the data to make more intelligent decisions. On the other hand, it is without a doubtthat nowadays the amount of data is exponentially increasing, and analysing large data sets has become a key basis of competition and innovation, underpinning new waves of productivity growth. This book aims to bring a fresh look onto the various ways that data science techniques could unleash value and drive productivity from these mountains of data.Researchers working in productivity analysis/data envelopment analysis will benefit from learning about the tools available in data science/big data that can be used in their current research analyses and endeavours. The data scientists, on the other hand, will also get benefit from learning about the plethora of applications available in productivity analysis/data envelopment analysis.
Data Science and Productivity Analytics
Charles, Vincent (Edited by)/ Aparicio, Juan (Edited by)/ Zhu, Joe (Edited by)
Idioma: Inglés
Editorial: Springer 2020
Serie: International Series in Operations Research & Management Science, Libro 280 de 323. Libro 280 de 323 - International Series in Operations Research & Management Science
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Librería: Revaluation Books, Exeter, , Reino UnidoRevaluation Books
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Hardcover. Condición: Brand New. 449 pages. 9.25x6.10x1.20 inches. In Stock.
Idioma: Inglés
Editorial: Springer 2020
Serie: International Series in Operations Research & Management Science, Libro 280 de 323. Libro 280 de 323 - International Series in Operations Research & Management Science
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Librería: Mispah books, Redhill, SURRE, Reino UnidoMispah books
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Hardcover. Condición: New. New. book.
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Editorial: Springer 2020
Serie: International Series in Operations Research & Management Science, Libro 280 de 323. Libro 280 de 323 - International Series in Operations Research & Management Science
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Librería: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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Condición: new. Questo è un articolo print on demand.
Idioma: Inglés
Editorial: Springer International Publishing Mai 2020 2020
Serie: International Series in Operations Research & Management Science, Libro 280 de 323. Libro 280 de 323 - International Series in Operations Research & Management Science
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, , AlemaniaBuchWeltWeit Ludwig Meier e.K.
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book includes a spectrum of concepts, such as performance, productivity, operations research, econometrics, and data science, for the practically and theoretically important areas of 'productivity analysis/data envelopment analysis' a…nd 'data science/big data'. Data science is defined as the collection of scientific methods, processes, and systems dedicated to extracting knowledge or insights from data and it develops on concepts from various domains, containing mathematics and statistical methods, operations research, machine learning, computer programming, pattern recognition, and data visualisation, among others.Examples of data science techniques include linear and logistic regressions, decision trees, Naïve Bayesian classifier, principal component analysis, neural networks, predictive modelling, deep learning, text analysis, survival analysis, and so on, all of which allow using the data to make more intelligent decisions. On the other hand, it is without a doubtthat nowadays the amount of data is exponentially increasing, and analysing large data sets has become a key basis of competition and innovation, underpinning new waves of productivity growth. This book aims to bring a fresh look onto the various ways that data science techniques could unleash value and drive productivity from these mountains of data.Researchers working in productivity analysis/data envelopment analysis will benefit from learning about the tools available in data science/big data that can be used in their current research analyses and endeavours. The data scientists, on the other hand, will also get benefit from learning about the plethora of applications available in productivity analysis/data envelopment analysis. 452 pp. Englisch.
Idioma: Inglés
Editorial: Springer International Publishing 2020
Serie: International Series in Operations Research & Management Science, Libro 280 de 323. Libro 280 de 323 - International Series in Operations Research & Management Science
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Librería: moluna, Greven, , Alemaniamoluna
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Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. First book to combine DEA and Data ScienceEditors and Contributors at the forefront of field worldwideIllustrates how Data Science techniques can unleash value and drive productivityVincent Charles is an exp…erienced researcher in the fiel.
Idioma: Inglés
Editorial: Springer 2020
Serie: International Series in Operations Research & Management Science, Libro 280 de 323. Libro 280 de 323 - International Series in Operations Research & Management Science
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Librería: Majestic Books, Hounslow, , Reino UnidoMajestic Books
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EUR 202,57
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Condición: New. Print on Demand.
Idioma: Inglés
Editorial: Springer 2020
Serie: International Series in Operations Research & Management Science, Libro 280 de 323. Libro 280 de 323 - International Series in Operations Research & Management Science
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Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
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EUR 202,36
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Condición: New. PRINT ON DEMAND.
Idioma: Inglés
Editorial: Springer, Springer Mai 2020 2020
Serie: International Series in Operations Research & Management Science, Libro 280 de 323. Libro 280 de 323 - International Series in Operations Research & Management Science
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000
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EUR 160,49
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Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book includes a spectrum of concepts, such as performance, productivity, operations research, econometrics, and data science, for the practically and theoretically important areas of ¿productivity analysis/data envelopment analysis¿ and ¿…data science/big datä. Data science is defined as the collection of scientific methods, processes, and systems dedicated to extracting knowledge or insights from data and it develops on concepts from various domains, containing mathematics and statistical methods, operations research, machine learning, computer programming, pattern recognition, and data visualisation, among others.Examples of data science techniques include linear and logistic regressions, decision trees, Naïve Bayesian classifier, principal component analysis, neural networks, predictive modelling, deep learning, text analysis, survival analysis, and so on, all of which allow using the data to make more intelligent decisions. On the other hand, it is without a doubtthat nowadays the amount of data is exponentially increasing, and analysing large data sets has become a key basis of competition and innovation, underpinning new waves of productivity growth. This book aims to bring a fresh look onto the various ways that data science techniques could unleash value and drive productivity from these mountains of data.Researchers working in productivity analysis/data envelopment analysis will benefit from learning about the tools available in data science/big data that can be used in their current research analyses and endeavours. The data scientists, on the other hand, will also get benefit from learning about the plethora of applications available in productivity analysis/data envelopment analysis.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 452 pp. Englisch.
