In this study, an attempt has been made to provide a comprehensive understanding of various ML algorithms that can be applied to enhance the intelligence of the business operations thereby leading to effective solutions for various business problems.
Authors
Arpit Singh, Assistant Professor, Jindal Global Business School, O.P. Jindal Global University, Sonipat, Haryana, India.
Ashish Dwivedi, Professor, Jindal Global Business School, O.P. Jindal Global University, Sonipat, Haryana, India.
Suchi Dubey, School of Business Education, MAHE Dubai, Dubai, UAE.
Vikas Lakhmani, Department of Mechanical Engineering, Indian Institute of Technology, Mumbai, India.
Summary
The copious amount of data generated as a result of Industry 4.0 revolution across every domain including Internet of things (IoT) data, cybersecurity data, business data, social data, and medical data has opened new avenues and business opportunities for organizations. The information imbibed in the data should be intelligently analysed to reap tangible benefits that can improve the efficiency of organizations. The knowledge of Artificial Intelligence (AI), and particularly Machine Learning (ML) algorithms is the requisite to decipher meanings and patterns in the data to gain useful insights.
Multiple ML algorithms namely supervised, unsupervised, semi-supervised, and reinforcement learning exists in this field. In this study, an attempt has been made to provide a comprehensive understanding of various ML algorithms that can be applied to enhance the intelligence of the business operations thereby leading to effective solutions for various business problems. The potential contribution of this study is to understand different ML techniques and its applications in various real world business problems such as e-commerce, manufacturing, healthcare, etc.
The major challenges and future research directions are presented in the study to further the research in the domain of ML. This study can be used as a reference to gain information about various prominent ML algorithms that have maximum utility in the business domain. Further, this study can assist researchers and practitioners in extending the knowledge to other business problems and aid in problem solving.
Published in: 2023 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE)
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