Department of Computer Science and Engineering, University Institute of Engineering and Technology, Kurukshetra University Kurukshetra, India.
International Journal of Science and Research Archive, 2025, 14(03), 1045-1054
Article DOI: 10.30574/ijsra.2025.14.3.0718
Received on 04 February 2025; revised on 15 March 2025; accepted on 17 March 2025
Deep learning technology which belongs to the machine learning domain has transformed corporate operations through both enhanced predictive capability and self-automation. Models developed from deep learning techniques process extensive information collections to reveal intricate patterns which provide organizations with useful knowledge through their operation as neural networks inspired from human brain functions. Different deep learning algorithms such as CNNs, RNNs and GANs together with autoencoders get analysed in this work while revealing their usefulness in healthcare along with retail and manufacturing and finance sectors. The text explores how deep learning functions to enhance supply chain effectiveness combined with better customer experiences while handling unstructured data effectively. The system's ability to trigger significant alterations is limited by its dependence on large computing power and substantial data utilization and difficult interpretation processes. Regularisation approaches and transfer learning alongside ethical AI frameworks should be used to resolve current difficulties so deep learning technology can achieve its fullest business impact. This paper provides an in-depth examination of deep learning applications alongside its benefits and obstacles which presents scanning views about its effect on company innovation development.
Deep Learning; Deep Learning Techniques; Application; Challenges
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ROHAN SAINI and CHANDER DIWAKER. Role of deep learning in business enterprises. International Journal of Science and Research Archive, 2025, 14(03), 1045-1054. Article DOI: https://doi.org/10.30574/ijsra.2025.14.3.0718.
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