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Programming Languages for Data Science

  2. 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
  3. 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.
  4. 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.
  5. 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.
  6. 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.