Machine Learning with R

R is a powerful language used widely for data analysis and statistical computing.and has many provisions to implement machine learning algorithms in a fast and simple manner.  Born in 1990 R is getting prominence today because of its simplicity.

• R is data analysis software: Data scientists can use R for statistical analysis, data visualization, and predictive modeling.
• R is a programming language: R is an object-oriented language & provides objects, operators, and functions that allow users to explore, model, and visualize data.
• R is an defacto environment for statistical analysis: Standard statistical methods are easy to implement in R, and since much of the cutting-edge research in statistics and predictive modeling is done in R, newly developed techniques are often available in R first.
• R is an open-source software project: R’s open interfaces allow it to integrate with other applications and systems.
• R community: The R project leadership has grown to include more than 20 leading statisticians and computer scientists from around the world, and thousands of contributors have created add-on packages. 

Take an example to understand the power of R language in today's collaborative open source world. The picture below shows heat map of a volcano is a R program of 15 lines that uses multiple R libraries developed by the community. 







And here are the lines of  R code that produced the above visualization :-




I will post more about R and why is it my ( actually all data scientist) favorite tool for data analysis. Mean while I am sharing a small  tutorial for beginners to R that is available at https://www.analyticsvidhya.com

A Complete Tutorial to learn Data Science in R from Scratch