PROGRAMMING LANGUAGES
USED FOR DATA SCIENCE

R :-
 Developed by Ross Ihaka & Robert Gentleman in the year 1993
 Programming Language & free software environment for Statistical Computing and graphical
methods.
 R includes Linear Regression, ML Algorithms , Time Series etc.
 R Contains many libraries which are mainly written in R itself but some of the libraries are
written in C, C++, FORTRAN .
 R is widely used for Academic purpose then some industries like HealthCare, Government,
Consulting etc.
 For Data Science, the popular programming languages are Python & R

Python:-
 Interpreted , high-level, general purpose programming language.
 It’s free , open-source software.
 Created by Guido Van Rossum in the Year 1991.
 It’s easy to learn python because the code is written in simple English language.
 Python is a popular Programming Language for Data Science.
 Pandas is a popular Data Analysis Library. Numpy is used for Numeric Analysis.
 Some other libraries are SciPy, Stats Models, Scikit-Learn etc.
 Micro Python Pyboard is used to write code on Micro Controllers and Embedded
Systems.

Julia:-
 It is high-level, high-performance, dynamic programming language.
 Developed by Jeff Bezanson
 It is well suited for numerical analysis & computational science.
 Julia is garbage collected and includes libraries for linear algebra, random number
generation and regular expression etc.
 Julia is fast and has math-friendly syntax, automatic memory management.

Scala:-
 It is general purpose programming language.
 Scala runs on Java Virtual Machine.
 It is also object-oriented and uses syntax of C Language.
 Designed by Martin Odersky and released in 2004
 Features of Scala includes val, Higher Order Functions, Partial Functions etc.

Swift:-
 It’s an open source , easy and flexible programming language.
 Developed by Apple for iOS
 Designed by Chris Lattner in 2014
 It performs tasks like numerical computation, high performance functions for
matrix math, digital signal processing, building machine learning models etc.
 Some of the popular libraries in swift are Nifty, Swift plot, Swift for TensorFlow.