International Journal of Statistics and Reliability Engineering

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Vol 10 ( Special Issue-1 ):

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Retrospective Analysis of Machine Learning Algorithms to Investigate Futuristic Implications

Abstract

A subfield of artificial intelligence known as machine learning (ML) explores algorithms that can learn on their own, straight from the incoming data. Every interaction and action taken using machine learning is something the system can learn from and apply the next time. This paper provides an overview of the research paper based on Machine Learning Algorithms whose citations are above 100 and uses in different areas from 2018- 2023. The paper begins the study by reviewing the fundamentals of machine learning and its algorithms. Further, it is discussed how ML can be used to make a difference in a number of fields in terms of applications and a comparative literature study of research paper whose citation is above 100 found on Google Scholar in various fields. These techniques enable computers to learn and act in a manner similar to how humans learn, i.e., by gaining knowledge from past data. The usage of machine learning (ML) techniques over the past five years is seen in Healthcare efficiency and medical services, traffic alerts (Google Map / GPS), social media / product recommendation, fraud/crime detection, agriculture, and others usages i.e. manufacturing, paraphrasing tools, weather prediction, industry, and many other fields. The presentation and organization of a thorough study of the recent machine learning algorithms used should make it easy for practitioners to get started in this area.

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ISSN(P) 2350-0174

ISSN(O) 2456-2378

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