Deep Learning Applications: An Overview

Authors

  • Akshita Rastogi
  • Rekha Jain

Abstract

It is essential that the data be handled with accuracy, and certain exercises are carried out so that the computers can think and act on their own, which is where the advanced time of Deep Learning comes in. A computer needs access to earlier information and interactions in order to think. The use of Deep Learning in diverse geographies will be discussed in this study. Many experiments have been conducted to increase the intelligence of machines. It is possible that learning is a human trait that has been adopted by robots as well. Many different systems serve the same objective. ANN, CNN, and RNN are some of the important algorithms for Deep learning applications. Deep learning is a subset of AI. Until yet, just a few applications of substantial knowledge have been studied. With Deep learning, it is possible to solve problems in hitherto untapped application areas and sub-areas. This study provides an overview of historical and future Deep Learning application domains, sub-areas, and applications. Using brain organization layers, deep learning aids in faster and more accurate adaptation to changes in the environment.

Published

2022-09-17