Beginning data science with R [electronic resource] /
Pathak, Manas A.author.
“Data Science with R” deals with implementing many useful data analysis methodologies with the R programming language. The target audience for this book is non-R programmers and non-statisticians. The book will cover all the necessary concepts from the basics to state-of-the-art technologies like working with big data. The author attempts to strike a balance between the “how”: specific processes and methodologies, while also talking about the “why”: giving an intuition behind how a particular technique works, so that the reader can apply the generalized solution to the problem at hand.
Description based upon print version of record.
Includes bibliographical references.
Introduction -- Overview of the R Programming Language -- Getting Data into R -- Data Visualization -- Exploratory Data Analysis -- Regression -- Classification -- Text Mining.  .
“Data Science with R” deals with implementing many useful data analysis methodologies with the R programming language. The target audience for this book is non-R programmers and non-statisticians. The book will cover all the necessary concepts from the basics to state-of-the-art technologies like working with big data. The author attempts to strike a balance between the “how”: specific processes and methodologies, while also talking about the “why”: giving an intuition behind how a particular technique works, so that the reader can apply the generalized solution to the problem at hand.
Applied mathematics.
Engineering mathematics.
Statistics .
Signal processing.
Image processing.
Speech processing systems.
R (Computer program language).
Mathematical and Computational Engineering.
Statistics and Computing/Statistics Programs.
Signal, Image and Speech Processing.