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Apache Spark for Data Science Cookbook

You're reading from   Apache Spark for Data Science Cookbook Solve real-world analytical problems

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Product type Paperback
Published in Dec 2016
Publisher
ISBN-13 9781785880100
Length 392 pages
Edition 1st Edition
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Authors (2):
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Padma Priya Chitturi Padma Priya Chitturi
Author Profile Icon Padma Priya Chitturi
Padma Priya Chitturi
Nagamallikarjuna Inelu Nagamallikarjuna Inelu
Author Profile Icon Nagamallikarjuna Inelu
Nagamallikarjuna Inelu
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Toc

Table of Contents (11) Chapters Close

Preface 1. Big Data Analytics with Spark 2. Tricky Statistics with Spark FREE CHAPTER 3. Data Analysis with Spark 4. Clustering, Classification, and Regression 5. Working with Spark MLlib 6. NLP with Spark 7. Working with Sparkling Water - H2O 8. Data Visualization with Spark 9. Deep Learning on Spark 10. Working with SparkR

Introduction

R is a flexible, open source, and powerful statistical programming language. It is preferred by many professional statisticians and researchers in a variety of fields. It has extensive statistical and graphical capabilities. R combines the aspects of functional and object-oriented programming. One of the key features of R is implicit looping, which yields compact, simple code and frequently leads to faster execution. It provides a command-line interpreted statistical computing environment with built-in scripting language.

R is an integrated suite of software facilities for data manipulation, calculation, and graphical display. Its key strengths are effective data handling and storage facility, and a collection of tools for data analysis. It provides a number of extensions that support data processing and machine learning tasks. However, interactive analysis in R is limited as the runtime is single-threaded and can only process datasets that fit in a single machine's memory...

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