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Mastering Data analysis with R
Mastering Data analysis with R

Mastering Data analysis with R: Gain sharp insights into your data and solve real-world data science problems with R—from data munging to modeling and visualization

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Full star icon Full star icon Full star icon Full star icon Half star icon 4.5 (2 Ratings)
Paperback Sep 2015 396 pages 1st Edition
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NZ$63.99 NZ$71.99
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NZ$89.99
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Arrow left icon
Profile Icon Daróczi
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Free Trial
Full star icon Full star icon Full star icon Full star icon Half star icon 4.5 (2 Ratings)
Paperback Sep 2015 396 pages 1st Edition
eBook
NZ$63.99 NZ$71.99
Paperback
NZ$89.99
Subscription
Free Trial
eBook
NZ$63.99 NZ$71.99
Paperback
NZ$89.99
Subscription
Free Trial

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Mastering Data analysis with R

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Description

Gain sharp insights into your data and solve real-world data science problems with R—from data munging to modeling and visualization About This Book Handle your data with precision and care for optimal business intelligence Restructure and transform your data to inform decision-making Packed with practical advice and tips to help you get to grips with data mining Who This Book Is For If you are a data scientist or R developer who wants to explore and optimize your use of R’s advanced features and tools, this is the book for you. A basic knowledge of R is required, along with an understanding of database logic. What You Will Learn Connect to and load data from R’s range of powerful databases Successfully fetch and parse structured and unstructured data Transform and restructure your data with efficient R packages Define and build complex statistical models with glm Develop and train machine learning algorithms Visualize social networks and graph data Deploy supervised and unsupervised classification algorithms Discover how to visualize spatial data with R In Detail R is an essential language for sharp and successful data analysis. Its numerous features and ease of use make it a powerful way of mining, managing, and interpreting large sets of data. In a world where understanding big data has become key, by mastering R you will be able to deal with your data effectively and efficiently. This book will give you the guidance you need to build and develop your knowledge and expertise. Bridging the gap between theory and practice, this book will help you to understand and use data for a competitive advantage. Beginning with taking you through essential data mining and management tasks such as munging, fetching, cleaning, and restructuring, the book then explores different model designs and the core components of effective analysis. You will then discover how to optimize your use of machine learning algorithms for classification and recommendation systems beside the traditional and more recent statistical methods. Style and approach Covering the essential tasks and skills within data science, Mastering Data Analysis provides you with solutions to the challenges of data science. Each section gives you a theoretical overview before demonstrating how to put the theory to work with real-world use cases and hands-on examples.

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Publication date : Sep 30, 2015
Length: 396 pages
Edition : 1st
Language : English
ISBN-13 : 9781783982028
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Product Details

Publication date : Sep 30, 2015
Length: 396 pages
Edition : 1st
Language : English
ISBN-13 : 9781783982028
Category :
Languages :
Concepts :

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Mastering Data analysis with R
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Table of Contents

16 Chapters
1. Hello, Data! Chevron down icon Chevron up icon
2. Getting Data from the Web Chevron down icon Chevron up icon
3. Filtering and Summarizing Data Chevron down icon Chevron up icon
4. Restructuring Data Chevron down icon Chevron up icon
5. Building Models (authored by Renata Nemeth and Gergely Toth) Chevron down icon Chevron up icon
6. Beyond the Linear Trend Line (authored by Renata Nemeth and Gergely Toth) Chevron down icon Chevron up icon
7. Unstructured Data Chevron down icon Chevron up icon
8. Polishing Data Chevron down icon Chevron up icon
9. From Big to Small Data Chevron down icon Chevron up icon
10. Classification and Clustering Chevron down icon Chevron up icon
11. Social Network Analysis of the R Ecosystem Chevron down icon Chevron up icon
12. Analyzing Time-series Chevron down icon Chevron up icon
13. Data Around Us Chevron down icon Chevron up icon
14. Analyzing the R Community Chevron down icon Chevron up icon
A. References Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.5
(2 Ratings)
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2 star 0%
1 star 0%
Fabien Deneuville Mar 27, 2016
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Ce livre est parfait pour les gens qui connaissent déjà bien R et veulent aller plus loin.J'ai découvert des choses que je ne soupçonnais pas, j'ai particulièrement apprécié le chapitre sur les graphes, celui sur les séries temporelles, le clustering... en fait il s'agit de zooms très utiles pour qui veut aller plus loin dans l'utilisation de R pour le data mining.
Amazon Verified review Amazon
Duncan W. Robinson Oct 29, 2015
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
I found "Mastering Data Analysis with R" useful & very readable. I especially liked the sections dealing with obtaining, filtering & manipulating data. Though some of this information can be found in various R package vignettes, much of it, including useful tips, is all in one place here. For example, I found the section on using functions from the R package "dplyr" useful for merging data sets. The reader of this book might do well to follow-up this volume with Hadley Wickham’s "Advanced R". I also enjoyed the treatment given to importing the corpus for text analysis. Python generally seems to be a bit easier to navigate for the pre-processing step when performing text analytics. This book made conducting the process in R much easier for me.
Amazon Verified review Amazon
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