Role of deep learning in business enterprises

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.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-30
DOI
https://doi.org/10.5281/zenodo.17034274
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
0.00
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article

Role of deep learning in business enterprises

Zenodo (CERN European Organization for Nuclear Research)
Geochemistry and Geologic Mapping
article

Role of deep learning in business enterprises

article en

Abstract

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.

Zenodo (CERN European Organization for Nuclear Research)
Kurukshetra University (IN)
Industry, innovation and infrastructure
Openalex Percentile: Top 55%
Geochemistry and Geologic Mapping
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Role of deep learning in business enterprises · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS