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Big Data Analytics with R

You're reading from   Big Data Analytics with R Leverage R Programming to uncover hidden patterns in your Big Data

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Product type Paperback
Published in Jul 2016
Publisher Packt
ISBN-13 9781786466457
Length 506 pages
Edition 1st Edition
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Author (1):
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Simon Walkowiak Simon Walkowiak
Author Profile Icon Simon Walkowiak
Simon Walkowiak
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Table of Contents (10) Chapters Close

Preface 1. The Era of Big Data FREE CHAPTER 2. Introduction to R Programming Language and Statistical Environment 3. Unleashing the Power of R from Within 4. Hadoop and MapReduce Framework for R 5. R with Relational Database Management Systems (RDBMSs) 6. R with Non-Relational (NoSQL) Databases 7. Faster than Hadoop - Spark with R 8. Machine Learning Methods for Big Data in R 9. The Future of R - Big, Fast, and Smart Data

Where to go next


After reading this book and going through all its tutorials you should have enough skills to let you perform scalable and distributed analysis of very large datasets using the R language. The usefulness of the material contained in this book hugely depends on other tools your current Big Data processing stack includes. Although we have presented you with a wide array of applications and frameworks which are common ingredients of Big Data workflows, for example Hadoop, Spark, SQL, and NoSQL databases, we appreciate that your personal needs and business requirements may vary.

In order to address your particular data-related problems and accomplish Big Data tasks, which may include a myriad of data analytics platforms, other programming languages, and various statistical methods or machine learning algorithms, you may need to develop a specific skill set and make sure to constantly grow your expertise in this dynamically evolving field. Throughout this book, we have included...

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