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Hardcover. Condition: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.
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Design and Modeling for Computer Experiments
Book 3 of 23: Chapman & Hall/CRC Computer Science & Data AnalysisLanguage: English
Published by Chapman and Hall/CRC, 2020
ISBN 10: 036757800X ISBN 13: 9780367578008
Condition: As New. Unread book in perfect condition.
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Design and Modeling for Computer Experiments
Book 3 of 23: Chapman & Hall/CRC Computer Science & Data AnalysisLanguage: English
Published by Chapman and Hall/CRC, 2020
ISBN 10: 036757800X ISBN 13: 9780367578008
Condition: New.
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Design and Modeling for Computer Experiments
Book 3 of 23: Chapman & Hall/CRC Computer Science & Data AnalysisLanguage: English
Published by Chapman and Hall/CRC, 2020
ISBN 10: 036757800X ISBN 13: 9780367578008
Condition: New. pp. 304.
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Hardcover. Condition: New. ISBN:9781032941752,Territorial restriction maybe printed on the book. This is an Int'l edition, ISBN and cover may differ from US edition, Contents same as US edition.
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Design and Modeling for Computer Experiments
Book 3 of 23: Chapman & Hall/CRC Computer Science & Data AnalysisLanguage: English
Published by Chapman and Hall/CRC, 2020
ISBN 10: 036757800X ISBN 13: 9780367578008
Condition: New. pp. 304.
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Design and Modeling for Computer Experiments
Book 3 of 23: Chapman & Hall/CRC Computer Science & Data AnalysisLanguage: English
Published by Chapman and Hall/CRC, 2020
ISBN 10: 036757800X ISBN 13: 9780367578008
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Design and Modeling for Computer Experiments
Book 3 of 23: Chapman & Hall/CRC Computer Science & Data AnalysisLanguage: English
Published by Chapman and Hall/CRC, 2020
ISBN 10: 036757800X ISBN 13: 9780367578008
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Design and Modeling for Computer Experiments
Book 3 of 23: Chapman & Hall/CRC Computer Science & Data AnalysisLanguage: English
Published by Chapman and Hall/CRC, 2020
ISBN 10: 036757800X ISBN 13: 9780367578008
Condition: New. pp. 304.
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Condition: New. Kai-Tai Fang, Runze Li, Agus SudjiantoComputer simulations based on mathematical models have become ubiquitous across the engineering disciplines and throughout the physical sciences. Successful use of a simulation model, however, requires.
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Statistical Foundations of Data Science
Book 7 of 36: Chapman & Hall/CRC Data ScienceLanguage: English
Published by Chapman and Hall/CRC, 2020
ISBN 10: 1466510846 ISBN 13: 9781466510845
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
£ 110.61
£ 15 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New.
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Statistical Foundations of Data Science
Book 7 of 36: Chapman & Hall/CRC Data ScienceLanguage: English
Published by Chapman and Hall/CRC, 2020
ISBN 10: 1466510846 ISBN 13: 9781466510845
Condition: New.
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Statistical Foundations of Data Science
Book 7 of 36: Chapman & Hall/CRC Data ScienceLanguage: English
Published by Chapman and Hall/CRC, 2020
ISBN 10: 1466510846 ISBN 13: 9781466510845
Condition: As New. Unread book in perfect condition.
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Design and Modeling for Computer Experiments
Book 3 of 23: Chapman & Hall/CRC Computer Science & Data AnalysisLanguage: English
Published by Taylor & Francis Group, 2005
ISBN 10: 1584885467 ISBN 13: 9781584885467
Condition: New. pp. xii + 290 Index.
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Design and Modeling for Computer Experiments (Chapman & Hall/CRC Computer Science & Data Analysis)
Book 3 of 23: Chapman & Hall/CRC Computer Science & Data AnalysisLanguage: English
Published by Chapman and Hall/CRC, 2005
ISBN 10: 1584885467 ISBN 13: 9781584885467
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 125.69
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
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Statistical Foundations of Data Science
Book 7 of 36: Chapman & Hall/CRC Data ScienceLanguage: English
Published by Chapman and Hall/CRC, 2020
ISBN 10: 1466510846 ISBN 13: 9781466510845
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
£ 129.44
£ 15 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: As New. Unread book in perfect condition.
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Statistical Foundations of Data Science (Chapman & Hall/CRC Data Science Series)
Book 7 of 36: Chapman & Hall/CRC Data ScienceLanguage: English
Published by Chapman and Hall/CRC 2020-08-17, 2020
ISBN 10: 1466510846 ISBN 13: 9781466510845
Hardcover. Condition: New.
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Statistical Foundations of Data Science (Chapman & Hall/CRC Data Science Series)
Book 7 of 36: Chapman & Hall/CRC Data ScienceLanguage: English
Published by Chapman and Hall/CRC, 2020
ISBN 10: 1466510846 ISBN 13: 9781466510845
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 132.73
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
-
Design and Modeling for Computer Experiments
Book 3 of 23: Chapman & Hall/CRC Computer Science & Data AnalysisLanguage: English
Published by Taylor & Francis Group, 2005
ISBN 10: 1584885467 ISBN 13: 9781584885467
Condition: New. pp. xii + 290, Abbreviations.
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Design and Modeling for Computer Experiments (Chapman & Hall/CRC Computer Science & Data Analysis)
Book 3 of 23: Chapman & Hall/CRC Computer Science & Data AnalysisLanguage: English
Published by Chapman and Hall/CRC, 2005
ISBN 10: 1584885467 ISBN 13: 9781584885467
hardcover. Condition: New. In shrink wrap. Looks like an interesting title!
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Statistical Foundations of Data Science
Book 7 of 36: Chapman & Hall/CRC Data ScienceLanguage: English
Published by Taylor and Francis Inc, US, 2020
ISBN 10: 1466510846 ISBN 13: 9781466510845
Hardback. Condition: New. Statistical Foundations of Data Science gives a thorough introduction to commonly used statistical models, contemporary statistical machine learning techniques and algorithms, along with their mathematical insights and statistical theories. It aims to serve as a graduate-level textbook and a research monograph on high-dimensional statistics, sparsity and covariance learning, machine learning, and statistical inference. It includes ample exercises that involve both theoretical studies as well as empirical applications.The book begins with an introduction to the stylized features of big data and their impacts on statistical analysis. It then introduces multiple linear regression and expands the techniques of model building via nonparametric regression and kernel tricks. It provides a comprehensive account on sparsity explorations and model selections for multiple regression, generalized linear models, quantile regression, robust regression, hazards regression, among others. High-dimensional inference is also thoroughly addressed and so is feature screening. The book also provides a comprehensive account on high-dimensional covariance estimation, learning latent factors and hidden structures, as well as their applications to statistical estimation, inference, prediction and machine learning problems. It also introduces thoroughly statistical machine learning theory and methods for classification, clustering, and prediction. These include CART, random forests, boosting, support vector machines, clustering algorithms, sparse PCA, and deep learning.
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Hardcover. Condition: Brand New. 1st edition. 304 pages. 9.25x6.25x1.00 inches. In Stock.
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Statistical Foundations of Data Science
Book 7 of 36: Chapman & Hall/CRC Data ScienceLanguage: English
Published by Taylor and Francis Inc, US, 2020
ISBN 10: 1466510846 ISBN 13: 9781466510845
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 5 out of 5 stars
Hardback. Condition: New. Statistical Foundations of Data Science gives a thorough introduction to commonly used statistical models, contemporary statistical machine learning techniques and algorithms, along with their mathematical insights and statistical theories. It aims to serve as a graduate-level textbook and a research monograph on high-dimensional statistics, sparsity and covariance learning, machine learning, and statistical inference. It includes ample exercises that involve both theoretical studies as well as empirical applications.The book begins with an introduction to the stylized features of big data and their impacts on statistical analysis. It then introduces multiple linear regression and expands the techniques of model building via nonparametric regression and kernel tricks. It provides a comprehensive account on sparsity explorations and model selections for multiple regression, generalized linear models, quantile regression, robust regression, hazards regression, among others. High-dimensional inference is also thoroughly addressed and so is feature screening. The book also provides a comprehensive account on high-dimensional covariance estimation, learning latent factors and hidden structures, as well as their applications to statistical estimation, inference, prediction and machine learning problems. It also introduces thoroughly statistical machine learning theory and methods for classification, clustering, and prediction. These include CART, random forests, boosting, support vector machines, clustering algorithms, sparse PCA, and deep learning.
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Condition: New. The authors are international authorities and leaders on the presented topics. All are fellows of the Institute of Mathematical Statistics and the American Statistical Association. Jianqing Fan is Frederick L. Moore Professor, Princeton Uni.
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Statistical Foundations of Data Science
Book 7 of 36: Chapman & Hall/CRC Data ScienceLanguage: English
Published by Taylor and Francis Inc, US, 2020
ISBN 10: 1466510846 ISBN 13: 9781466510845
Hardback. Condition: New. Statistical Foundations of Data Science gives a thorough introduction to commonly used statistical models, contemporary statistical machine learning techniques and algorithms, along with their mathematical insights and statistical theories. It aims to serve as a graduate-level textbook and a research monograph on high-dimensional statistics, sparsity and covariance learning, machine learning, and statistical inference. It includes ample exercises that involve both theoretical studies as well as empirical applications.The book begins with an introduction to the stylized features of big data and their impacts on statistical analysis. It then introduces multiple linear regression and expands the techniques of model building via nonparametric regression and kernel tricks. It provides a comprehensive account on sparsity explorations and model selections for multiple regression, generalized linear models, quantile regression, robust regression, hazards regression, among others. High-dimensional inference is also thoroughly addressed and so is feature screening. The book also provides a comprehensive account on high-dimensional covariance estimation, learning latent factors and hidden structures, as well as their applications to statistical estimation, inference, prediction and machine learning problems. It also introduces thoroughly statistical machine learning theory and methods for classification, clustering, and prediction. These include CART, random forests, boosting, support vector machines, clustering algorithms, sparse PCA, and deep learning.
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Statistical Foundations of Data Science
Book 7 of 36: Chapman & Hall/CRC Data ScienceLanguage: English
Published by Taylor and Francis Inc, US, 2020
ISBN 10: 1466510846 ISBN 13: 9781466510845
Hardback. Condition: New. Statistical Foundations of Data Science gives a thorough introduction to commonly used statistical models, contemporary statistical machine learning techniques and algorithms, along with their mathematical insights and statistical theories. It aims to serve as a graduate-level textbook and a research monograph on high-dimensional statistics, sparsity and covariance learning, machine learning, and statistical inference. It includes ample exercises that involve both theoretical studies as well as empirical applications.The book begins with an introduction to the stylized features of big data and their impacts on statistical analysis. It then introduces multiple linear regression and expands the techniques of model building via nonparametric regression and kernel tricks. It provides a comprehensive account on sparsity explorations and model selections for multiple regression, generalized linear models, quantile regression, robust regression, hazards regression, among others. High-dimensional inference is also thoroughly addressed and so is feature screening. The book also provides a comprehensive account on high-dimensional covariance estimation, learning latent factors and hidden structures, as well as their applications to statistical estimation, inference, prediction and machine learning problems. It also introduces thoroughly statistical machine learning theory and methods for classification, clustering, and prediction. These include CART, random forests, boosting, support vector machines, clustering algorithms, sparse PCA, and deep learning.
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International EditionSTATISTICAL FOUNDATIONS OF DATA SCIENCE
Published by T&F INDIA, 2026
ISBN 10: 1032941758 ISBN 13: 9781032941752
Hardcover. Condition: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 7-12 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
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Condition: New. Brand New, Softcover edition. This item may ship from the US or our Overseas warehouse depending on your location and stock availability.
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Statistical Learning for High-Dimensional Data
Published by Chapman & Hall, 2020
ISBN 10: 1466510846 ISBN 13: 9781466510845
Hardcover. Condition: Brand New. 600 pages. 9.50x6.25x1.50 inches. In Stock.
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Hardcover. Condition: Brand New. 1st edition. 304 pages. 9.25x6.25x1.00 inches. In Stock. This item is printed on demand.
