2024, Vol. 6, Special Issue 6, Part C
How deep learning improves the process of data analysis in data science
Author(s): Sucheta Mor and Palak Kalsi
Abstract: In past few years, there is increase in applications of Machine Learning and this is because of Introduction to Deep Learning with characteristic of recognizing patterns on big data sets. It provides better result than conventional models. In data science there is always focus on big data sets, that leads to better decision making. Deep Learning and Data Analysis both having characteristic of pattern recognition which led them to proceed simultaneously. Deep learning become most revolutionized technology of Artificial Intelligence due to abilities of prediction, analyze big data sets and provide some chrematistics that can’t be obtain previously.
As, AI is basically a concept of working of machine as human and for now AI can accomplish tasks those are difficult and only possible by natural intelligence behind this huge success the main role is played by Deep Learning. The basic difference that makes deep learning models different from conventional models is focuses on programming as well as on training of data set from real world.
In this Paper, we will explore what is deep learning, applications of deep learning, how it is different from other conventional models, what is data science, major steps in process of data analysis, how deep learning helpful in process of data analysis and provide better and fast result than before.
DOI: 10.33545/27068919.2024.v6.i6c.1240Pages: 190-193 | Views: 1128 | Downloads: 130Download Full Article: Click Here
How to cite this article:
Sucheta Mor, Palak Kalsi.
How deep learning improves the process of data analysis in data science. Int J Adv Acad Stud 2024;6(6S):190-193. DOI:
10.33545/27068919.2024.v6.i6c.1240