A Review on Data Science Techniques

Authors

  • Ruta Kulkarni Department of Electronics and Telecommunication Engineering, MKSSS's Cummins College of Engineering for Women, Pune, India
  • Tanvi Pardhi Department of Electronics and Telecommunication Engineering, MKSSS's Cummins College of Engineering for Women, Pune, India

Keywords:

data science, decision tree, linear regression, clustering, machine learning, support-vector machine

Abstract

The term data science has garnered a huge attention in the past few decades and various research is being conducted in this field. There are a variety of techniques and technologies that are being developed and used in the field of data science. Data science is a blend of various techniques, technologies and theories – machine learning, statistics, data mining, mathematics and many other domains. It mostly deals with an aim of using the data strategically and such that we can gain insights from that data. This domain has experienced a boom because of the huge quantity of data that we are trying to collect and process in the last few decades. This review is about the different techniques related to data science and how they come into play according to the type of data that we handle.

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Published

04-10-2021

How to Cite

[1]
R. Kulkarni and T. Pardhi, “A Review on Data Science Techniques”, IJRESM, vol. 4, no. 9, pp. 239–241, Oct. 2021.

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Section

Articles