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- PublisherRoutledge
- Publication date2020
- ISBN 10 0367738198
- ISBN 13 9780367738198
- BindingPaperback
- LanguageEnglish
- Edition number1
- Number of pages352
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Parallel Computing for Data Science (Chapman & Hall/CRC The R Series)
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Parallel Computing for Data Science: With Examples in R, C++ and CUDA
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Taylor & Francis Ltd, 2020
ISBN 10: 0367738198
ISBN 13: 9780367738198
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Paperback / softback. Condition: New. New copy - Usually dispatched within 4 working days. 185. Seller Inventory # B9780367738198
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Parallel Computing for Data Science: With Examples in R, C++ and Cuda
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Paperback. Condition: Brand New. 328 pages. 9.21x6.14x0.91 inches. In Stock. Seller Inventory # __0367738198
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Parallel Computing for Data Science (Chapman & Hall/CRC The R Series)
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Parallel Computing for Data Science
Print on DemandSeller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Parallel Computing for Data Science: With Examples in R, C++ and CUDA is one of the first parallel computing books to concentrate exclusively on parallel data structures, algorithms, software tools, and applications in data science. It includes examples not only from the classic 'n observations, p variables' matrix format but also from time series, network graph models, and numerous other structures common in data science. The examples illustrate the range of issues encountered in parallel programming.With the main focus on computation, the book shows how to compute on three types of platforms: multicore systems, clusters, and graphics processing units (GPUs). It also discusses software packages that span more than one type of hardware and can be used from more than one type of programming language. Readers will find that the foundation established in this book will generalize well to other languages, such as Python and Julia. 328 pp. Englisch. Seller Inventory # 9780367738198
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Parallel Computing for Data Science (Chapman & Hall/CRC The R Series)
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Parallel Computing for Data Science w/ Examples in R, C++, CUBA
Seller: LIBRERIA LEA+, Santiago, RM, Chile
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Blanda. Condition: New. Dust Jacket Condition: Nuevo. No Aplica (illustrator). 1. ".a thorough, but readable guide to parallel computing?one that can be used by researchers and students in a wide range of disciplines. In my view, this book will meet that need. ? For me and colleagues in my field, I would see this as a ?must-have? reference book." David E. Giles, University of Victoria. "This is a book that I will use, both as a reference and for instruction. The examples are poignant and the presentation moves the reader directly from concept to working code." Michael Kane, Yale University. Parallel Computing for Data Science: With Examples in R, C++ and CUDA is one of the first parallel computing books to concentrate exclusively on parallel data structures, algorithms, software tools, and applications in data science. It includes examples not only from the classic "n observations, p variables" matrix format but also from time series, network graph models, and numerous other structures common in data science. The book also discusses software packages that span more than one type of hardware and can be used from more than one type of programming language. Dr. Norman Matloff is a professor of computer science at the University of California, Davis, where he was a founding member of the Department of Statistics. He is a statistical consultant and a former database software developer. He earned a PhD in pure mathematics from UCLA. 480 gr. Libro. Seller Inventory # 9780367738198LEA88973
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Parallel Computing for Data Science : With Examples in R, C++ and Cuda
Print on DemandSeller: AHA-BUCH GmbH, Einbeck, Germany
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Parallel Computing for Data Science: With Examples in R, C++ and CUDA is one of the first parallel computing books to concentrate exclusively on parallel data structures, algorithms, software tools, and applications in data science. It includes examples not only from the classic 'n observations, p variables' matrix format but also from time series, network graph models, and numerous other structures common in data science. The examples illustrate the range of issues encountered in parallel programming.With the main focus on computation, the book shows how to compute on three types of platforms: multicore systems, clusters, and graphics processing units (GPUs). It also discusses software packages that span more than one type of hardware and can be used from more than one type of programming language. Readers will find that the foundation established in this book will generalize well to other languages, such as Python and Julia. Seller Inventory # 9780367738198
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Parallel Computing for Data Science
Print on DemandSeller: moluna, Greven, Germany
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Dr. Norman Matloff is a professor of computer science at the University of California, Davis, where he was a founding member of the Department of Statistics. He is a statistical consultant and a former database software developer. He has. Seller Inventory # 594600591
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