Produktbild: Parallel Computing for Data Science
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Parallel Computing for Data Science With Examples in R, C++ and CUDA

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64,99 € UVP 79,70 €

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

18.12.2020

Verlag

Taylor & Francis

Seitenzahl

354

Maße (L/B/H)

23,4/15,6/1,9 cm

Gewicht

538 g

Sprache

Englisch

ISBN

978-0-367-73819-8

Beschreibung

Rezension

"From my reading of the book, Matloff achieves his goals, and in doing so he has provided a volume that will be immensely useful to a very wide audience. I can see it being used as a reference by data analysts, statisticians, engineers, econometricians, biometricians, etc. This would apply to both established researchers and graduate students. This book provides exactly the sort of information that this audience is looking for, and it is presented in a very accessible and friendly manner."
-Econometrics Beat: Dave Giles' Blog, July 2015

"The author has correctly recognized that there is a pressing need for 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-one that would be well thumbed!"
-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

"Matloff's Parallel Computing for Data Science: With Examples in R, C++ and CUDA can be recommended to colleagues and students alike, and the author is to be congratulated for taming a difficult and exhaustive body of topics via a very accessible primer."
-Dirk Eddelbuettel, Debian and R Projects

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

18.12.2020

Verlag

Taylor & Francis

Seitenzahl

354

Maße (L/B/H)

23,4/15,6/1,9 cm

Gewicht

538 g

Sprache

Englisch

ISBN

978-0-367-73819-8

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: gpsr@libri.de

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  • Produktbild: Parallel Computing for Data Science
  • Introduction to Parallel Processing in R. "Why Is My Program So Slow?": Obstacles to Speed. Principles of Parallel Loop Scheduling. The Shared Memory Paradigm: A Gentle Introduction through R. The Shared Memory Paradigm: C Level. The Shared Memory Paradigm: GPUs. Thrust and Rth. The Message Passing Paradigm. MapReduce Computation. Parallel Sorting and Merging. Parallel Prefix Scan. Parallel Matrix Operations. Inherently Statistical Approaches: Subset Methods. Appendices.