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Idioma: Inglés
Publicado por Springer International Publishing, 2021
ISBN 10: 3030497224 ISBN 13: 9783030497224
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 64,19
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides an introduction to quantitative marketing with Python. The book presents a hands-on approach to using Python for real marketing questions, organized by key topic areas. Following the Python scientific computing movement toward reproducible research, the book presents all analyses in Colab not Elektronisches Buch, which integrate code, figures, tables, and annotation in a single file. The code not Elektronisches Buch for each chapter may be copied, adapted, and reused in one's own analyses. The book also introduces the usage of machine learning predictive models using the Python sklearn package in the context of marketing research.This book is designed for three groups of readers: experienced marketing researchers who wish to learn to program in Python, coming from tools and languages such as R, SAS, or SPSS; analysts or students who already program in Python and wish to learn about marketing applications; and undergraduate or graduate marketing students with little or no programming background. It presumes only an introductory level of familiarity with formal statistics and contains a minimum of mathematics.
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Añadir al carritoTaschenbuch. Condición: Neu. Python for Marketing Research and Analytics | Jason S. Schwarz (u. a.) | Taschenbuch | xi | Englisch | 2021 | Springer | EAN 9783030497224 | 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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Publicado por Springer International Publishing Nov 2021, 2021
ISBN 10: 3030497224 ISBN 13: 9783030497224
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides an introduction to quantitative marketing with Python. The book presents a hands-on approach to using Python for real marketing questions, organized by key topic areas. Following the Python scientific computing movement toward reproducible research, the book presents all analyses in Colab not Elektronisches Buch, which integrate code, figures, tables, and annotation in a single file. The code not Elektronisches Buch for each chapter may be copied, adapted, and reused in one's own analyses. The book also introduces the usage of machine learning predictive models using the Python sklearn package in the context of marketing research.This book is designed for three groups of readers: experienced marketing researchers who wish to learn to program in Python, coming from tools and languages such as R, SAS, or SPSS; analysts or students who already program in Python and wish to learn about marketing applications; and undergraduate or graduate marketing students with little or no programming background. It presumes only an introductory level of familiarity with formal statistics and contains a minimum of mathematics. 284 pp. Englisch.
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Idioma: Inglés
Publicado por Springer, Berlin|Springer International Publishing|Springer, 2021
ISBN 10: 3030497224 ISBN 13: 9783030497224
Librería: moluna, Greven, Alemania
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Añadir al carritoKartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book provides an introduction to quantitative marketing with Python. This book is designed for three groups of readers: experienced marketing researchers who wish to learn to program in Python, coming from tools and languages such as R, SAS, or SPSS.
Idioma: Inglés
Publicado por Springer, Palgrave Macmillan Nov 2021, 2021
ISBN 10: 3030497224 ISBN 13: 9783030497224
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 64,19
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book provides an introduction to quantitative marketing with Python. The book presents a hands-on approach to using Python for real marketing questions, organized by key topic areas. Following the Python scientific computing movement toward reproducible research, the book presents all analyses in Colab not Elektronisches Buch, which integrate code, figures, tables, and annotation in a single file. The code not Elektronisches Buch for each chapter may be copied, adapted, and reused in one's own analyses. The book also introduces the usage of machine learning predictive models using the Python sklearn package in the context of marketing research.This book is designed for three groups of readers: experienced marketing researchers who wish to learn to program in Python, coming from tools and languages such as R, SAS, or SPSS; analysts or students who already program in Python and wish to learn about marketing applications; and undergraduate or graduate marketing students with little or no programming background. It presumes only an introductory level of familiarity with formal statistics and contains a minimum of mathematics.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 284 pp. Englisch.