Majumder, Ruhul Quddus (2025) Machine Learning for Predictive Analytics: Trends and Future Directions. International Journal of Innovative Science and Research Technology, 10 (4): 25apr1899. pp. 3557-3564. ISSN 2456-2165
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Abstract
Machine Learning has become an integral part of predictive analysis, empowering organizations to identify and analyze trends, uncover patterns, and make data-driven decisions across diverse domains. This review explores the evolution of machine learning procedures in predictive analysis and advancements, emerging trends and future scope. The deployment of predictive analysis techniques, highlighted, along with the usage of machine learning technologies for predicted modelling and the many possibilities for prediction analysis in various arenas. This paper also discusses what the emerging and future domains are where machine learning can be used for automation and maximizing the output. The evolution of machine learning (ML) and deep learning (DL) and their application in predictive data investigation has deeply influenced as it can derive data-driven insights. This paper also discusses how predictive analysis can be used to optimize security concerns and vulnerabilities and how it can detect and predict threats in the system.
Item Type: | Article |
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Subjects: | L Education > L Education (General) |
Depositing User: | Editor IJISRT Publication |
Date Deposited: | 15 May 2025 10:16 |
Last Modified: | 15 May 2025 10:16 |
URI: | https://eprint.ijisrt.org/id/eprint/885 |