Gergely Daroczi

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
About This BookHandle your data with precision and care for optimal business intelligenceRestructure and transform your data to inform decision-makingPacked with practical advice and tips to help you get to grips with data miningWho This Book Is ForIf 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 LearnConnect to and load data from R's range of powerful databasesSuccessfully fetch and parse structured and unstructured dataTransform and restructure your data with efficient R packagesDefine and build complex statistical models with glmDevelop and train machine learning algorithmsVisualize social networks and graph dataDeploy supervised and unsupervised classification algorithmsDiscover how to visualize spatial data with RIn DetailR 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 approachCovering 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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  • Igor Alyoshinhar citeretfor 2 år siden
    Besides GET requests, you can easily interact with RESTful API endpoints via POST, DELETE, or PUT requests as well by using the postForm function from the RCurl package or the httpDELETE, httpPUT, or httpHEAD functions— see details about the httr package later.
  • Igor Alyoshinhar citeretfor 2 år siden
    HTTPS is not a separate protocol alongside HTTP, but instead HTTP over an encrypted SSL/TLS connection.
  • Igor Alyoshinhar citeretfor 2 år siden
    it is also said, that around 80 percent of data analysis is spent cleaning data.

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