Hardcover. Condizione: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.
Condizione: As New. Unread book in perfect condition.
Condizione: New.
Da: Majestic Books, Hounslow, Regno Unito
EUR 66,76
Quantità: 3 disponibili
Aggiungi al carrelloCondizione: New. pp. 304.
Lingua: Inglese
Editore: T And F India, 2026
Da: Books in my Basket, New Delhi, India
EUR 58,83
Quantità: 20 disponibili
Aggiungi al carrelloHardcover. Condizione: 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.
Condizione: New. pp. 304.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 66,25
Quantità: 10 disponibili
Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 70,05
Quantità: 10 disponibili
Aggiungi al carrelloCondizione: New.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 77,20
Quantità: 3 disponibili
Aggiungi al carrelloCondizione: New. pp. 304.
Da: moluna, Greven, Germania
EUR 68,02
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: 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.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 132,00
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: New.
Condizione: New. pp. xii + 290 Index.
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: As New. Unread book in perfect condition.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 149,99
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. In.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 154,47
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Lingua: Inglese
Editore: Chapman and Hall/CRC 2020-08-17, 2020
ISBN 10: 1466510846 ISBN 13: 9781466510845
Da: Chiron Media, Wallingford, Regno Unito
EUR 152,47
Quantità: 2 disponibili
Aggiungi al carrelloHardcover. Condizione: New.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 158,39
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. In.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 157,57
Quantità: 3 disponibili
Aggiungi al carrelloCondizione: New. pp. xii + 290, Abbreviations.
hardcover. Condizione: New. In shrink wrap. Looks like an interesting title!
Lingua: Inglese
Editore: Taylor and Francis Inc, US, 2020
ISBN 10: 1466510846 ISBN 13: 9781466510845
Da: Rarewaves USA, OSWEGO, IL, U.S.A.
Hardback. Condizione: 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.
Lingua: Inglese
Editore: Taylor and Francis Inc, US, 2020
ISBN 10: 1466510846 ISBN 13: 9781466510845
Da: Rarewaves.com USA, London, LONDO, Regno Unito
EUR 210,03
Quantità: 1 disponibili
Aggiungi al carrelloHardback. Condizione: 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.
Da: Revaluation Books, Exeter, Regno Unito
EUR 196,19
Quantità: 2 disponibili
Aggiungi al carrelloHardcover. Condizione: Brand New. 1st edition. 304 pages. 9.25x6.25x1.00 inches. In Stock.
Da: moluna, Greven, Germania
EUR 164,72
Quantità: 2 disponibili
Aggiungi al carrelloCondizione: 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.
Lingua: Inglese
Editore: Taylor and Francis Inc, US, 2020
ISBN 10: 1466510846 ISBN 13: 9781466510845
Da: Rarewaves USA United, OSWEGO, IL, U.S.A.
Hardback. Condizione: 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.
Lingua: Inglese
Editore: Taylor and Francis Inc, US, 2020
ISBN 10: 1466510846 ISBN 13: 9781466510845
Da: Rarewaves.com UK, London, Regno Unito
EUR 198,83
Quantità: 1 disponibili
Aggiungi al carrelloHardback. Condizione: 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.
Editore: T&F INDIA, 2026
ISBN 10: 1032941758 ISBN 13: 9781032941752
Da: UK BOOKS STORE, London, LONDO, Regno Unito
EUR 84,99
Quantità: 20 disponibili
Aggiungi al carrelloHardcover. Condizione: 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.
ISBN 10: 1032941758 ISBN 13: 9781032941752
Da: SMASS Sellers, IRVING, TX, U.S.A.
Condizione: New. Brand New, Softcover edition. This item may ship from the US or our Overseas warehouse depending on your location and stock availability.
Editore: Chapman & Hall, 2020
ISBN 10: 1466510846 ISBN 13: 9781466510845
Da: Revaluation Books, Exeter, Regno Unito
EUR 239,53
Quantità: 2 disponibili
Aggiungi al carrelloHardcover. Condizione: Brand New. 600 pages. 9.50x6.25x1.50 inches. In Stock.
Da: Majestic Books, Hounslow, Regno Unito
EUR 138,72
Quantità: 3 disponibili
Aggiungi al carrelloCondizione: New. pp. xii + 290 Illus. This item is printed on demand.