Mastering Data Analysis With R
by Gergely Daroczi /
2013 / English / PDF
7.6 MB Download
Gain sharp insights into your data and solve real-world data science problems with Rfrom 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.
