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R High Performance Programming (Anglais) Broché – 29 janvier 2015

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Description du produit

Présentation de l'éditeur

Overcome performance difficulties in R with a range of exciting techniques and solutions

About This Book

  • Benchmark and profile R programs to solve performance bottlenecks
  • Combine the ease of use and flexibility of R with the power of big data tools
  • Filled with practical techniques and useful code examples to process large data sets more efficiently

Who This Book Is For

This book is for programmers and developers who want to improve the performance of their R programs by making them run faster with large data sets or who are trying to solve a pesky performance problem.

What You Will Learn

  • Benchmark and profile R programs to solve performance bottlenecks
  • Understand how CPU, memory, and disk input/output constraints can limit the performance of R programs
  • Optimize R code to run faster and use less memory
  • Use compiled code in R and other languages such as C to speed up computations
  • Harness the power of GPUs for computational speed
  • Process data sets that are larger than memory using disk-based memory and chunking
  • Tap into the capacity of multiple CPUs using parallel computing
  • Leverage the power of advanced database systems and Big Data tools from within R

In Detail

With the increasing use of information in all areas of business and science, R provides an easy and powerful way to analyze and process the vast amounts of data involved. It is one of the most popular tools today for faster data exploration, statistical analysis, and statistical modeling and can generate useful insights and discoveries from large amounts of data.

Through this practical and varied guide, you will become equipped to solve a range of performance problems in R programming. You will learn how to profile and benchmark R programs, identify bottlenecks, assess and identify performance limitations from the CPU, identify memory or disk input/output constraints, and optimize the computational speed of your R programs using great tricks, such as vectorizing computations. You will then move on to more advanced techniques, such as compiling code and tapping into the computing power of GPUs, optimizing memory consumption, and handling larger-than-memory data sets using disk-based memory and chunking.

Biographie de l'auteur

Aloysius Lim

Aloysius Lim has a knack for translating complex data and models into easy-to-understand insights. As cofounder of About People, a data science and design consultancy, he loves solving problems and helping others to find practical solutions to business challenges using data. His breadth of experience―7 years in the government, education, and retail industries―equips him with unique perspectives to find creative solutions.



William Tjhi

William Tjhi is a data scientist with years of experience working in academia, government, and industry. He began his data science journey as a PhD candidate researching new algorithms to improve the robustness of high-dimensional data clustering. Upon receiving his doctorate, he moved from basic to applied research, solving problems among others in molecular biology and epidemiology using machine learning. He published some of his research in peer-reviewed journals and conferences. With the rise of Big Data, William left academia for industry, where he started practicing data science in both business and public sector settings. William is passionate about R and has been using it as his primary analysis tool since his research days. He was once part of Revolution Analytics, and there he contributed to make R more suitable for Big Data.

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Commentaires client les plus utiles sur Amazon.com

Amazon.com: 4,5 sur 5 étoiles 13 commentaires
5,0 sur 5 étoilesQuite readable and doesn't waste time on a bunch of trivial introductory stuff
le 10 juin 2016 - Publié sur Amazon.com
Achat vérifié
3 personnes ont trouvé cela utile.
3,0 sur 5 étoilesTwo good books trying to coexist in one body
le 5 mars 2015 - Publié sur Amazon.com
3 personnes ont trouvé cela utile.
5,0 sur 5 étoilesPractical examples and detailed explanations
le 22 mars 2015 - Publié sur Amazon.com
Une personne a trouvé cela utile.
5,0 sur 5 étoilesAloysius and William cover the code execution benchmarking techniques at the beginning very well and then make you embark on won
le 23 février 2015 - Publié sur Amazon.com
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