Chen Lincy (16 results)

Condition: Brand New. New.SoftCover International edition. Different ISBN and Cover image but contents are same as US edition.Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

Condition: As New. Unread book in perfect condition.

Paperback / softback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days. Klinger, Jenna; Kobylski, Luke; Celis, JP; Chen, Lincy; Bowlus, Hannah (illustrator).

Condition: New.

Condition: New.

Condition: New.

Condition: As New. Unread book in perfect condition.

Condition: New.

Condition: New. 1st edition NO-PA16APR2015-KAP.

Condition: New. In English.

Condition: New.

Hardback. Condition: New. 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.…

Hardcover. Condition: Brand New. 320 pages. 9.19x6.13x9.21 inches. In Stock.

Hardback. Condition: New. 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.…

Paperback. Condition: new. Paperback. Our clever Mr. Frog loves a mystery and also enjoys fun and games. In this installment, Mr. Frog gets tricked into a game of hide and seek with some mischievous kittens. It will take all of his talents and the assistance of the barnyard inhabitants to help find the crafty kittens. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Klinger, Jenna; Kobylski, Luke; Celis, JP; Chen, Lincy; Bowlus, Hannah (illustrator).…

Condition: 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.…