R Programming for Data Science and Machine Learning

R LANGUAGE

R language is an open–source programming language that is used for statistical analysis and graphical representation. It was developed by Ross Ihaka and Robert Gentleman, at the University of Auckland, New Zealand. R contains a large and coherent system of statistical and graphical techniques that can be used for data analysis. It provides a well–defined environment for reproducible research.

R is an implementation of S programming language, inspired by Scheme. A lot of data scientists, statisticians, analysts etc. use R to make sense of the data and then use it for data analysis, predictive analysis and data visualization. The data analysis can be done by writing scripts and functions in R language. It is an object–oriented language that provides modeling, exploring and visualizing of the data. The process of data analysis is usually done in a few lines of code. R provides all the functions regarding data manipulation, statistical model or chart that an analyst could need. It includes machine learning algorithms, linear aggression, time series, statistical interference etc. R is written in its own language which makes programmers to understand the format easily, but for heavy computations it collaborates with C, C++, Python, etc.

Features

Open–source

R language provides an open–source, free of cost platform. It is licensed by GNU, General Public License, this means that anyone can download it and make changes in it according to the prerequisites. Many other packages are available under the same license and can be downloaded easily.