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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM25371

A Study on Deep Learning as a Frontier of Machine Learning

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM25371

Volume:

7 |

8 |

Aug 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

K

Khushi

PN

Preeti Negi

SK

Simanjeet Kaur

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Abstract

Because of advancements and the advent of deep learning, there has been a revolution in machine learning applications in recent years. Deep learning models are superior to traditional machine learning models because they include more learning layers and a greater level of abstraction. This benefit is further supported by the fact that all components of the model directly learn from the data. Conventional machine learning models experience limits as a result of the method they use to process the data because of the growing volume of data and the increased desire to derive useful insights from the data. The increase in data volume has led to the development of more sophisticated learning algorithms that are quicker and more accurate. Every firm will undoubtedly utilize a model like this one that produces the most accurate predictions in order to stay ahead of the competition. We shall discuss some of the most widely used deep learning techniques in this paper.

KEYWORDS

Neural networks machine learning and deep learning.

Cite This Article

Khushi, Preeti Negi, Simanjeet Kaur, "A Study on Deep Learning as a Frontier of Machine Learning," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 8, Aug 2023.

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Publication Date

8/23/2023

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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