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Cover: 9798987654316 | Predictive Analytics and Machine Learning for Managers | Espinosa
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Predictive Analytics and Machine Learning for Managers
Taschenbuch von J. Alberto Espinosa
Sprache: Englisch

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Beschreibung
This book was written by the architect of two MS Analytics programs and one undergraduate specialization in Business Analytics, with over a decade of experience teaching and practicing predictive analytics, and co-chairing premier academic conference mini-track in this field. The author's goal is to provide strong but understandable conceptual foundations and practical material for graduate students and managers, describing how to frame a business question, identify various model specification (i.e., feature engineering) and model methods (explainable and black box), select the optimal model based on the bias, variance, and cross-validation testing, and interpret results with meaningful storytelling for clients and managers. The book contains two components: (1) the main text with two sections-one with conceptual, mathematical, and managerial foundations, the other about advanced predictive modeling methods based on machine learning. The main text is further subdivided into two sections-Section 1 contains basic fundamentals of statistics and predictive modeling; Section 2 provides a deeper discussion of machine learning and advance predictive modeling approaches based on machine learning and cross-validation methods; and (2) a free appendix companion with annotated R Markdown code with hands-on applications, posted in GitHub.
This book was written by the architect of two MS Analytics programs and one undergraduate specialization in Business Analytics, with over a decade of experience teaching and practicing predictive analytics, and co-chairing premier academic conference mini-track in this field. The author's goal is to provide strong but understandable conceptual foundations and practical material for graduate students and managers, describing how to frame a business question, identify various model specification (i.e., feature engineering) and model methods (explainable and black box), select the optimal model based on the bias, variance, and cross-validation testing, and interpret results with meaningful storytelling for clients and managers. The book contains two components: (1) the main text with two sections-one with conceptual, mathematical, and managerial foundations, the other about advanced predictive modeling methods based on machine learning. The main text is further subdivided into two sections-Section 1 contains basic fundamentals of statistics and predictive modeling; Section 2 provides a deeper discussion of machine learning and advance predictive modeling approaches based on machine learning and cross-validation methods; and (2) a free appendix companion with annotated R Markdown code with hands-on applications, posted in GitHub.
Details
Erscheinungsjahr: 2023
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 352
ISBN-13: 9798987654316
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Espinosa, J. Alberto
Hersteller: Jibe4Fun Press
Maße: 229 x 152 x 21 mm
Von/Mit: J. Alberto Espinosa
Erscheinungsdatum: 20.04.2023
Gewicht: 0,572 kg
preigu-id: 126883409
Details
Erscheinungsjahr: 2023
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 352
ISBN-13: 9798987654316
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Espinosa, J. Alberto
Hersteller: Jibe4Fun Press
Maße: 229 x 152 x 21 mm
Von/Mit: J. Alberto Espinosa
Erscheinungsdatum: 20.04.2023
Gewicht: 0,572 kg
preigu-id: 126883409
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