Taimre thomas (54 risultati)

Solutions Manual to Accompany Simulation and the Monte Carlo Method (Wiley Series in Probability and Statistics)
Kroese, Dirk P.; Taimre, Thomas; Botev, Zdravko I.; Rubinstein, Reuven Y.
Lingua: Inglese
Editore: Wiley-Interscience, 2007
Serie: Libro 209 di 358 - Wiley Series in Probability and Statistics
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Da: My Dead Aunt's Books, Hyattsville, MD, U.S.A.My Dead Aunt's Books
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EUR 21,48
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paperback. Condizione: Very Good. Unmarked trade paperback. Gentle bend on corner of cover.

Data Science and Machine Learning: Mathematical and Statistical Methods (Chapman & Hall/CRC Machine Learning & Pattern Recognition)
Vaisman, Radislav,Taimre, Thomas,Botev, Zdravko I.,Kroese, Dirk P.
Lingua: Inglese
Editore: Chapman and Hall/CRC, 2019
Serie: Libro 15 di 15 - Chapman & Hall/Crc Machine Learning & Pattern Recognition
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Da: HPB-Red, Dallas, TX, U.S.A.HPB-Red
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EUR 33,28
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Hardcover. Condizione: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.

Data Science and Machine Learning: Mathematical and Statistical Methods (Chapman & Hall/CRC Machine Learning & Pattern Recognition)
Botev, Zdravko; Kroese, Dirk P.; Taimre, Thomas; Vaisman, Radislav
Lingua: Inglese
Editore: Chapman and Hall/CRC, 2019
Serie: Libro 15 di 15 - Chapman & Hall/Crc Machine Learning & Pattern Recognition
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Da: World of Books (was SecondSale), Montgomery, IL, U.S.A.World of Books (was SecondSale)
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EUR 36,66
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Condizione: Very Good. Item in very good condition! Textbooks may not include supplemental items i.e. CDs, access codes etc.

Simulation and the Monte Carlo Method
Kroese, Dirk P.; Taimre, Thomas; Botev, Zdravko I.; Rubinstein, Reuven Y.
Lingua: Inglese
Editore: Wiley-Interscience, 2007
Serie: Libro 209 di 358 - Wiley Series in Probability and Statistics
- Brossura
Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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EUR 36,69
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Condizione: As New. Unread book in perfect condition.

Simulation and the Monte Carlo Method
Kroese, Dirk P.; Taimre, Thomas; Botev, Zdravko I.; Rubinstein, Reuven Y.
Lingua: Inglese
Editore: Wiley-Interscience, 2007
Serie: Libro 209 di 358 - Wiley Series in Probability and Statistics
- Brossura
Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 40,57
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Condizione: New.

Solutions Manual to Accompany Simulation and the Monte Carlo Method
Kroese Dirk P. Rubinstein Reuven Y. Botev Zdravko I. Taimre Thomas
Lingua: Inglese
Editore: John Wiley & Sons, 2007
Serie: Libro 209 di 358 - Wiley Series in Probability and Statistics
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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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EUR 45,19
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Condizione: New. pp. 188.

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Da: Books From California, Simi Valley, CA, U.S.A.Books From California
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hardcover. Condizione: Fine.

Simulation and the Monte Carlo Method
Kroese, Dirk P.; Taimre, Thomas; Botev, Zdravko I.; Rubinstein, Reuven Y.
Lingua: Inglese
Editore: Wiley-Interscience, 2007
Serie: Libro 209 di 358 - Wiley Series in Probability and Statistics
- Brossura
Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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EUR 36,83
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Condizione: New.

Solutions Manual to Accompany Simulation and the Monte Carlo Method
Dirk P. Kroese Reuven Y. Rubinstein Zdravko I. Botev Thomas Taimre
Lingua: Inglese
Editore: John Wiley & Sons, 2007
Serie: Libro 209 di 358 - Wiley Series in Probability and Statistics
- Brossura
Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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EUR 55,81
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Condizione: New. pp. 188 2nd Edition.

Simulation and the Monte Carlo Method
Kroese, Dirk P.; Taimre, Thomas; Botev, Zdravko I.; Rubinstein, Reuven Y.
Lingua: Inglese
Editore: Wiley-Interscience, 2007
Serie: Libro 209 di 358 - Wiley Series in Probability and Statistics
- Brossura
Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
Contatta il venditoreVenditore con 5 stelleCondizione: Usato - Come nuovo
EUR 42,09
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Condizione: As New. Unread book in perfect condition.

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Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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EUR 97,84
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Condizione: New.

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Da: California Books, Miami, FL, U.S.A.California Books
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EUR 107,41
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Condizione: New.

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Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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Condizione: As New. Unread book in perfect condition.

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Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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Condizione: New.

Lingua: Inglese
Editore: Wiley Dez 2007, 2007
Serie: Libro 209 di 358 - Wiley Series in Probability and Statistics
- Brossura
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 54,50
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Taschenbuch. Condizione: Neu. Neuware - This accessible new edition explores the major topics in Monte Carlo simulationSimulation and the Monte Carlo Method, Second Edition reflects the latest developments in the field and presents a fully updated and comprehensive account of the major topics that have emerged in Monte Carlo sim…ulation since the publication of the classic First Edition over twenty-five years ago. While maintaining its accessible and intuitive approach, this revised edition features a wealth of up-to-date information that facilitates a deeper understanding of problem solving across a wide array of subject areas, such as engineering, statistics, computer science, mathematics, and the physical and life sciences.The book begins with a modernized introduction that addresses the basic concepts of probability, Markov processes, and convex optimization. Subsequent chapters discuss the dramatic changes that have occurred in the field of the Monte Carlo method, with coverage of many modern topics including:Markov Chain Monte CarloVariance reduction techniques such as the transform likelihood ratio method and the screening methodThe score function method for sensitivity analysisThe stochastic approximation method and the stochastic counter-part method for Monte Carlo optimizationThe cross-entropy method to rare events estimation and combinatorial optimizationApplication of Monte Carlo techniques for counting problems, with an emphasis on the parametric minimum cross-entropy methodAn extensive range of exercises is provided at the end of each chapter, with more difficult sections and exercises marked accordingly for advanced readers. A generous sampling of applied examples is positioned throughout the book, emphasizing various areas of application, and a detailed appendix presents an introduction to exponential families, a discussion of the computational complexity of stochastic programming problems, and sample MATLAB(r) programs.Requiring only a basic, introductory knowledge of probability and statistics, Simulation and the Monte Carlo Method, Second Edition is an excellent text for upper-undergraduate and beginning graduate courses in simulation and Monte Carlo techniques. The book also serves as a valuable reference for professionals who would like to achieve a more formal understanding of the Monte Carlo method.

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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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Condizione: New.

Data Science and Machine Learning: Mathematical and Statistical Methods (Chapman & Hall/CRC Machine Learning & Pattern Recognition)
Botev, Zdravko Zdravko Botev, Dirk P. Kroese, Thomas Taimre,
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Da: Chiron Media, Wallingford, Regno UnitoChiron Media
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hardcover. Condizione: New.

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Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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Condizione: New.

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Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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Condizione: As New. Unread book in perfect condition.

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Da: California Books, Miami, FL, U.S.A.California Books
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Condizione: New.

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Condizione: acceptable. Used - Acceptable: All pages and the cover are intact, but shrink wrap, dust covers, or boxed set case may be missing. Pages may include limited notes, highlighting, or minor water damage but the text is readable. Pages may include limited notes and highlighting, but the text cannot be obscured or unreada…ble. Any access codes or passwords originally included with the book may be expired, used or no longer valid. Image is stock photo and cover art edition may be different than pictured.

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Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
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Condizione: New. In.

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Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
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Condizione: New. In.

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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Condizione: New.

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Da: California Books, Miami, FL, U.S.A.California Books
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EUR 136,95
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Condizione: New.

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Da: Rarewaves USA, OSWEGO, IL, U.S.A.Rarewaves USA
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Hardback. Condizione: New. 2nd. Praise for the first edition:"In nine succinct but information-packed chapters, the authors provide a logically structured and robust introduction to the mathematical and statistical methods underpinning the still-evolving field of AI and data science."- Joacim Rocklöv and Albert A. Gayle, Interna…tional Journal of Epidemiology, Volume 49, Issue 6"This book organizes the algorithms clearly and cleverly. The way the Python code was written follows the algorithm closely-very useful for readers who wish to understand the rationale and flow of the background knowledge."- Yin-Ju Lai and Chuhsing Kate Hsiao, Biometrics, Volume 77, Issue 4The purpose of Data Science and Machine Learning: Mathematical and Statistical Methods is to provide an accessible, yet comprehensive textbook intended for students interested in gaining a better understanding of the mathematics and statistics that underpin the rich variety of ideas and machine learning algorithms in data science.New in the Second EditionThis expanded edition provides updates across key areas of statistical learning: Monte Carlo Methods: A new section introducing regenerative rejection sampling - a simpler alternative to MCMC. Unsupervised Learning: Inclusion of two multidimensional diffusion kernel density estimators, as well as the bandwidth perturbation matching method for the optimal data-driven bandwidth selection. Regression: New automatic bandwidth selection for local linear regression. Feature Selection and Shrinkage: A new chapter introducing the klimax method for model selection in high-dimensions. Reinforcement Learning: A new chapter on contemporary topics such as policy iteration, temporal difference learning, and policy gradient methods, all complete with Python code. Appendices: Expanded treatment of linear algebra, functional analysis, and optimization that includes the coordinate-descent method and the novel Majorization-Minimization method for constrained optimization.Key Features:Focuses on mathematical understanding.Presentation is self-contained, accessible, and comprehensive.Extensive list of exercises and worked-out examples.Many concrete algorithms with Python code.Full color throughout and extensive indexing.A single-counter consecutive numbering of all theorems, definitions, equations, etc., for easier text searches.

Data Science and Machine Learning : Mathematical and Statistical Methods, 1st Edition
Botev, Zdravko; Kroese, Dirk P.; Taimre, Thomas; Vaisman, Radislav
Lingua: Inglese
Editore: Taylor & Francis Group, 2019
Serie: Libro 15 di 15 - Chapman & Hall/Crc Machine Learning & Pattern Recognition
- Rilegato
Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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EUR 127,59
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Condizione: New.

- Rilegato
Da: Rarewaves.com USA, London, LONDO, Regno UnitoRarewaves.com USA
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 156,00
Spedizione gratuitaSpedito da Regno Unito a U.S.A.Quantità: 2 disponibili
Hardback. Condizione: New. 2nd. Praise for the first edition:"In nine succinct but information-packed chapters, the authors provide a logically structured and robust introduction to the mathematical and statistical methods underpinning the still-evolving field of AI and data science."- Joacim Rocklöv and Albert A. Gayle, Interna…tional Journal of Epidemiology, Volume 49, Issue 6"This book organizes the algorithms clearly and cleverly. The way the Python code was written follows the algorithm closely-very useful for readers who wish to understand the rationale and flow of the background knowledge."- Yin-Ju Lai and Chuhsing Kate Hsiao, Biometrics, Volume 77, Issue 4The purpose of Data Science and Machine Learning: Mathematical and Statistical Methods is to provide an accessible, yet comprehensive textbook intended for students interested in gaining a better understanding of the mathematics and statistics that underpin the rich variety of ideas and machine learning algorithms in data science.New in the Second EditionThis expanded edition provides updates across key areas of statistical learning: Monte Carlo Methods: A new section introducing regenerative rejection sampling - a simpler alternative to MCMC. Unsupervised Learning: Inclusion of two multidimensional diffusion kernel density estimators, as well as the bandwidth perturbation matching method for the optimal data-driven bandwidth selection. Regression: New automatic bandwidth selection for local linear regression. Feature Selection and Shrinkage: A new chapter introducing the klimax method for model selection in high-dimensions. Reinforcement Learning: A new chapter on contemporary topics such as policy iteration, temporal difference learning, and policy gradient methods, all complete with Python code. Appendices: Expanded treatment of linear algebra, functional analysis, and optimization that includes the coordinate-descent method and the novel Majorization-Minimization method for constrained optimization.Key Features:Focuses on mathematical understanding.Presentation is self-contained, accessible, and comprehensive.Extensive list of exercises and worked-out examples.Many concrete algorithms with Python code.Full color throughout and extensive indexing.A single-counter consecutive numbering of all theorems, definitions, equations, etc., for easier text searches.

- Brossura
Da: Books Puddle, New York, NY, U.S.A.Books Puddle
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 155,74
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Condizione: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.

Data Science and Machine Learning
Zdravko Botev (University of New South Wales)|Dirk P. Kroese|Thomas Taimre
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Da: moluna, Greven, Germaniamoluna
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EUR 112,86
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Condizione: New. Zdravko I. Botev, PhD, is the pioneer of several modern statistical methodologies, including the diffusion kernel density estimator, the generalized splitting method for rare-event simulation, the bandwidth perturbation matching.