Condizione: As New. Unread book in perfect condition.
EUR 107,71
Quantità: 3 disponibili
Aggiungi al carrelloCondizione: New.
Condizione: New.
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: New.
EUR 103,24
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Condizione: New. 1st edition NO-PA16APR2015-KAP.
EUR 114,01
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. In.
EUR 114,41
Quantità: 1 disponibili
Aggiungi al carrelloHardback. Condizione: New. New copy - Usually dispatched within 4 working days. 585.
EUR 114,00
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
EUR 122,81
Quantità: 3 disponibili
Aggiungi al carrelloCondizione: New.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 124,12
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
EUR 152,72
Quantità: 2 disponibili
Aggiungi al carrelloHardcover. Condizione: Brand New. 320 pages. 9.19x6.13x9.21 inches. In Stock.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 256,23
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: As New. Unread book in perfect condition.
Da: PBShop.store US, Wood Dale, IL, U.S.A.
EUR 122,01
Quantità: Più di 20 disponibili
Aggiungi al carrelloHRD. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
EUR 118,14
Quantità: Più di 20 disponibili
Aggiungi al carrelloHRD. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 101,80
Quantità: 2 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Written by an experienced statistics educator and two data scientists, this book unifies conventional statistical thinking and contemporary machine learning framework into a single overarching umbrella over data science. The book is designed to bridge the knowledge gap between conventional statistics and machine learning. It provides an accessible approach for readers with a basic statistics background to develop a mastery of machine learning. The book starts with elucidating examples in Chapter 1 and fundamentals on refined optimization in Chapter 2, which are followed by common supervised learning methods such as regressions, classification, support vector machines, tree algorithms, and range regressions. After a discussion on unsupervised learning methods, it includes a chapter on unsupervised learning and a chapter on statistical learning with data sequentially or simultaneously from multiple resources.One of the distinct features of this book is the comprehensive coverage of the topics in statistical learning and medical applications. It summarizes the authors' teaching, research, and consulting experience in which they use data analytics. The illustrating examples and accompanying materials heavily emphasize understanding on data analysis, producing accurate interpretations, and discovering hidden assumptions associated with various methods.Key Features:Unifies conventional model-based framework and contemporary data-driven methods into a single overarching umbrella over data science.Includes real-life medical applications in hypertension, stroke, diabetes, thrombolysis, aspirin efficacy.Integrates statistical theory with machine learning algorithms.Includes potential methodological developments in data science. 298 pp. Englisch.
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 128,61
Quantità: Più di 20 disponibili
Aggiungi al carrelloHardback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
Da: moluna, Greven, Germania
EUR 93,92
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. John T. Chen is a professor of Statistics at Bowling Green State University. He completed his postdoctoral training at McMaster University (Canada) after earning a PhD degree in statistics at the University of Sydney (Australia). John has publishe.
Da: CitiRetail, Stevenage, Regno Unito
EUR 125,74
Quantità: 1 disponibili
Aggiungi al carrelloHardcover. Condizione: new. Hardcover. Written by an experienced statistics educator and two data scientists, this book unifies conventional statistical thinking and contemporary machine learning framework into a single overarching umbrella over data science. The book is designed to bridge the knowledge gap between conventional statistics and machine learning. It provides an accessible approach for readers with a basic statistics background to develop a mastery of machine learning. The book starts with elucidating examples in Chapter 1 and fundamentals on refined optimization in Chapter 2, which are followed by common supervised learning methods such as regressions, classification, support vector machines, tree algorithms, and range regressions. After a discussion on unsupervised learning methods, it includes a chapter on unsupervised learning and a chapter on statistical learning with data sequentially or simultaneously from multiple resources.One of the distinct features of this book is the comprehensive coverage of the topics in statistical learning and medical applications. It summarizes the authors teaching, research, and consulting experience in which they use data analytics. The illustrating examples and accompanying materials heavily emphasize understanding on data analysis, producing accurate interpretations, and discovering hidden assumptions associated with various methods.Key Features:Unifies conventional model-based framework and contemporary data-driven methods into a single overarching umbrella over data science.Includes real-life medical applications in hypertension, stroke, diabetes, thrombolysis, aspirin efficacy.Integrates statistical theory with machine learning algorithms.Includes potential methodological developments in data science. This book unifies conventional statistical thinking and contemporary machine learning framework into a single overarching umbrella over data science. The book is designed to bridge the knowledge gap between conventional statistics and machine learning. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 114,46
Quantità: 1 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Written by an experienced statistics educator and two data scientists, this book unifies conventional statistical thinking and contemporary machine learning framework into a single overarching umbrella over data science. The book is designed to bridge the knowledge gap between conventional statistics and machine learning. It provides an accessible approach for readers with a basic statistics background to develop a mastery of machine learning. The book starts with elucidating examples in Chapter 1 and fundamentals on refined optimization in Chapter 2, which are followed by common supervised learning methods such as regressions, classification, support vector machines, tree algorithms, and range regressions. After a discussion on unsupervised learning methods, it includes a chapter on unsupervised learning and a chapter on statistical learning with data sequentially or simultaneously from multiple resources.One of the distinct features of this book is the comprehensive coverage of the topics in statistical learning and medical applications. It summarizes the authors' teaching, research, and consulting experience in which they use data analytics. The illustrating examples and accompanying materials heavily emphasize understanding on data analysis, producing accurate interpretations, and discovering hidden assumptions associated with various methods.Key Features:Unifies conventional model-based framework and contemporary data-driven methods into a single overarching umbrella over data science.Includes real-life medical applications in hypertension, stroke, diabetes, thrombolysis, aspirin efficacy.Integrates statistical theory with machine learning algorithms.Includes potential methodological developments in data science.
Da: preigu, Osnabrück, Germania
EUR 117,20
Quantità: 5 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. Statistical Prediction and Machine Learning | John Tuhao Chen (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2024 | Chapman and Hall/CRC | EAN 9780367332273 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.