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Paper ID:IJSREM63911

Applications of machine learning in various sectors

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM63911

Volume:

10 |

5 |

May 2026

Pages:

1-7

Publication Frequency:

Monthly (12 issues per year)

DOI
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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

Samiksha Milind Parve

Samiksha Milind Parve

P. G. Department of Computer Science

Pro. Ram Meghe Institute of Technology and Research

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Saloni Vilas Tale

Saloni Vilas Tale

P. G. Department of Computer Science

Pro. Ram Meghe Institute of Technology and Research

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SI

Samrudhi Inzalkar

P. G. Department of Computer Science

Pro. Ram Meghe Institute of Technology and Research

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Abstract

Machine learning (ML) has become a transformative force across multiple domains, enabling automated decision-making, predictive analytics, and intelligent data processing. This review explores the broad spectrum of ML applications, including supervised, unsupervised, and reinforcement learning, across industries such as healthcare, finance, cybersecurity, education, transportation, agriculture, and energy. By analyzing recent advancements, different ML techniques address domain specific challenges and enhance operational efficiency. Additionally, this work provides insights for researchers and practitioners seeking to harness ML for real-world applications.

KEYWORDS

Keywords: Machine Learning Supervised Machine Learning Unsupervised Machine Learning Deep Learning Artificial Intelligence

Cite This Article

Samiksha Milind Parve, Saloni Vilas Tale, Samrudhi Inzalkar, "Applications of machine learning in various sectors," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 5, pp. 1-7, May 2026.

Full Article/Conclusion

Machine Learning has become a powerful technology that is transforming various sectors such as healthcare, finance, agriculture, education, transportation, and cybersecurity. By enabling intelligent automation, prediction, and data-driven decision-making, ML improves efficiency, accuracy, and productivity across industries.   This study highlights the different types of Machine Learning and their real-world applications in multiple domains. Although ML offers significant advantages, challenges such as data privacy, bias, and high computational cost still need to be addressed.   With continuous advancements in Artificial Intelligence and data technologies, Machine Learning is expected to play an even greater role in developing smart, secure, and efficient systems in the future.    

References

1]   K. A. Singh, (2025). The role of Machine learning in various sectors: A Comprehensive review. INTERNATIONAL JOURNAL for Research in Applied Science and Engineering Technology,              13(5),              3152–3159. https://doi.org/10.22214/ijraset.2025.70952 https://www.irjet.net/archives/V9/i3/IRJET- V9I3274.pdf 2]   A. Dhoke et al., Kadam, S., & Sungare, S. (2018).Machine learning: Trends and applications [Journal-article]. International Journal of Advance Research, Ideas and Innovations in Technology, 1567–1568. 3]     D. B., Nandalwar, J. I., & Sable, P. S. (2023). Machine learning – its applications, benefits, and threats. INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND  MANAGEMENT,         07(03). https://doi.org/10.55041/ijsrem18228     4]     Kumar, S., & CGCIJCTR. (2023). Applications of Machine Learning in Diverse sector: A study. CGC International Journal of Contemporary Technology and Research, 5(2), 344–344. https://doi.org/10.46860/cgcijctr.2024.01.10.344    5]   P. International Research Journal of Engineering and Technology (IRJET), & Keraleeya Samajam’s Model College. (2022). Research Paper on Machine Learning and its application. International Research Journal of Engineering and  Technology  (IRJET),  09(03),  1483. 6]   Shiramshetty, S. K., Mothey, M., Annam, S., & Bussa, S. (2024). Machine learning applications in telecom and banking. Integrated Journal for Research in Arts and Humanities, 57–69. https://doi.org/10.55544/ijrah.4.6.8 7] Kamepalli, S., & Srinivasa Rao, B. (2019). Recent Applications of Machine Learning: A survey. In International Journal of Innovative Technology and Exploring Engineering (IJITEE) (Vol. 8, Issue 6C2, pp. 263–264). 8]        Waqas, M., Naseem, A., Humphries, U. W., Hlaing, P. T., Dechpichai, P., Wangwongchai, A., The Joint Graduate School of Energy and Environment (JGSEE), King Mongkut’s University of Technology Thonburi (KMUTT), Bangkok,  34190, Thailand. (2025). Applications of machine learning and deep learning in agriculture: A comprehensive review [Journal-article]. Green Technologies and Sustainability,3,     100199. https://doi.org/10.1016/j.grets.2025.100199   9]      J. D., Da Costa, E. J., Da Costa, J. P. J.,Silvestre, A. S. S., Canedo, E. D., Rocha, H. S.,University of Brasilia (UnB), Department of Electrical Engineering, Lippe Innovations UG, University of Applied Sciences in Business Administration (FHDW), & Hochschule Hamm- Lippstadt            (HSHL),         University                  of              Applied Sciences. (2025). AI-driven modern slavery detection for supply chain: A cross-jurisdictional legal text analysis. In Machine Learning With Applications (Vols. 23–23, p. 100827) [Journal- article]. https://doi.org/10.1016/j.mlwa.2025.100827 10]    Giudici, P., Kolesnikov, V., & Department Of Economics and management.University of Pavia. (2026). SAFE AI metrics: Integrate approach https://doi.org/10.1016/j.mlwa.2025.100821

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Publication Date

5/24/2026

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