Parallel Computing for Data Science by Norman Matloff
This is one of the first parallel computing books to focus exclusively on parallel data structures, algorithms, software tools, and applications in data science. The book prepares readers to write effective parallel code in various languages and learn more about different R packages and other tools. It covers the classic n observations, p varia-
Advanced R
-
Using R for Introductory Statistics
-
R Markdown
-
Statistical Computing with R, Second Edition
-
Hands-On Machine Learning with R
-
Graphical Data Analysis with R
-
Introduction to Scientific Programming and Simulation Using R
-
Advanced R, Second Edition
-
Extending R
-
Reproducible Research with R and R Studio
-
Work Automation with R
- R for Social Network Analysis
-
Stated Preference Methods Using R
-
Introduction to Forestry Data Analysis with R
-
Simulation and Power Analysis Using R
-
R and MATLAB
-
The Essentials of Data Science: Knowledge Discovery Using R
-
blogdown
-
Statistical Computing in C++ and R
-
Model-Based Clustering, Classification, and Density Estimation Using mclust in R
-
Using R for Modelling and Quantitative Methods in Fisheries
-
Analyzing Baseball Data with R
-
Computational Actuarial Science with R
-
Using the R Commander
-
Implementing Reproducible Research
-
R for Conservation and Development Projects
-
Distributions for Modeling Location, Scale, and Shape
-
Interactive Web-Based Data Visualization with R, plotly, and shiny
-
R Markdown Cookbook
-
Learn R
-
Interactively Exploring High-Dimensional Data and Models in R
-
Displaying Time Series, Spatial, and Space-Time Data with R
-
Copula Additive Distributional Regression Using R
-
Introductory Fisheries Analyses with R
-
Introduction to Political Analysis in R
-
Engineering Production-Grade Shiny Apps
"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 audienceI 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
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 published numerous articles in prestigious journals, such as the ACM Transactions on Database Systems, ACM Transactions on Modeling and Computer Simulation, Annals of Probability, Biometrika, Communications of the ACM, and IEEE Transactions on Data Engineering. He earned a PhD in pure mathematics from UCLA, specializing in probability/functional analysis and statistics.
| SKU | Unavailable |
| ISBN 13 | 9780367738198 |
| ISBN 10 | 0367738198 |
| Title | Parallel Computing for Data Science |
| Author | Norman Matloff |
| Series | Chapman And Hall Crc The R Series |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Routledge |
| Year published | 2020-12-18 |
| Number of pages | 328 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |