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R Data Analysis Cookbook

Posted By: AlenMiler
R Data Analysis Cookbook

R Data Analysis Cookbook by Viswa Viswanathan
English | 30 May 2015 | ISBN: 1783989068 | 342 Pages | EPUB/MOBI/PDF (True) | 27.14 MB

Data analysis has recently emerged as a very important focus for a huge range of organizations and businesses. R makes detailed data analysis easier, making advanced data exploration and insight accessible to anyone interested in learning it.

This book empowers you by showing you ways to use R to generate professional analysis reports. It provides examples for various important analysis and machine-learning tasks that you can try out with associated and readily available data. The book also teaches you to quickly adapt the example code for your own needs and save yourself the time needed to construct code from scratch.

Key Features

Analyse data with ready-to-use and customizable recipes
Discover convenient functions to speed-up your work and data files
Explore the leading R packages built for expert data analysis

What you will learn

Get data into your R environment and prepare it for analysis
Perform exploratory data analyses and generate meaningful visualizations of the data
Apply several machine-learning techniques for classification and regression
Get your hands around large data sets with the help of reduction techniques
Extract patterns from time-series data and produce forecasts based on them
Learn how to extract actionable information from social network data
Implement geospatial analysis
Present your analysis convincingly through reports and build an infrastructure to enable others to play with your data

About the Author

Viswa Viswanathan is an associate professor of Computing and Decision Sciences at the Stillman School of Business in Seton Hall University. After completing his PhD in artificial intelligence, Viswa spent a decade in academia and then switched to a leadership position in the software industry for a decade.

Shanthi Viswanathan is an experienced technologist who has delivered technology management and enterprise architecture consulting to many enterprise customers. She has worked for Infosys Technologies, Oracle Corporation, and Accenture. As a consultant, Shanthi has helped several large organizations, such as Canon, Cisco, Celgene, Amway, Time Warner Cable, and GE among others, in areas such as data architecture and analytics, master data management, service-oriented architecture, business process management, and modeling.

Table of Contents

Acquire and Prepare the Ingredients – Your Data
What's in There? – Exploratory Data Analysis
Where Does It Belong? – Classification
Give Me a Number – Regression
Can You Simplify That? – Data Reduction Techniques
Lessons from History – Time Series Analysis
It's All about Your Connections – Social Network Analysis
Put Your Best Foot Forward – Document and Present Your Analysis
Work Smarter, Not Harder – Efficient and Elegant R Code
Where in the World? – Geospatial Analysis
Playing Nice – Connecting to Other Systems