Author(s): Neha Bhateja, Nishu Sethi, Shivangi Kaushal

Email(s): Email ID Not Available

DOI: 10.52711/2349-2988.2021.00033   

Address: Neha Bhateja, Nishu Sethi, Shivangi Kaushal
Department of Computer Science, Amity University, Haryana, Gurugram 122413, Haryana, India.
*Corresponding Author

Published In:   Volume - 13,      Issue - 3,     Year - 2021


ABSTRACT:
Machine learning as a branch of Artificial Intelligence is growing at a very rapid pace. It has shown significant benefits across a number of different industry verticals in helping them improve their productivity and making them less reliant on humans. The success and the growth of any industry depends on the manageability of massive data, using the data for predictions and deriving business value, automating the processes without the need of human intervention, provide satisfactory services to their clients and the security of client's information. Machine learning is a method that provides a way to transform the processes that leads to growth by using the statistical methods. The focus of this paper is to provide an overview of machine learning and highlight the various areas where machine learning is implemented by the business organizations and industries.


Cite this article:
Neha Bhateja, Nishu Sethi, Shivangi Kaushal. Machine Learning and its role in Diverse Business Systems. Research Journal of Science and Technology. 2021; 13(3):213-7. doi: 10.52711/2349-2988.2021.00033

Cite(Electronic):
Neha Bhateja, Nishu Sethi, Shivangi Kaushal. Machine Learning and its role in Diverse Business Systems. Research Journal of Science and Technology. 2021; 13(3):213-7. doi: 10.52711/2349-2988.2021.00033   Available on: https://rjstonline.com/AbstractView.aspx?PID=2021-13-3-9


REFERENCES:
1.    R. Cioffi, M. Travaglioni, G. Piscitelli, A. Petrillo and F. De Felice, "Artificial Intelligence and Machine Learning Applications in Smart Production: Progress, Trends, and Directions", Sustainability, vol. 12, no. 2, p. 492, 2020. Available: 10.3390/su12020492.
2.    M. Attaran and P. Deb, "Machine Learning: The New 'Big Thing' for Competitive Advantage", International Journal of Knowledge Engineering and Data Mining, vol. 5, no. 1, p. 1, 2018. Available: 10.1504/ijkedm.2018.10015621.
3.    Leo Dencelin X, Ramkumar T. Distributed Machine Learning Algorithms to classify Protein secondary structures for Drug Design – A Survey. Research J. Pharm. and Tech. 2017; 10(9): 3173-3180. doi: 10.5958/0974-360X.2017.00564.9
4.    Das, K. and Beher, R.N. (2017) ‘A survey on machine learning: concept, algorithms and applications’, International Journal of Innovative Research in Computer and Communication Engineering, February, Vol. 5, No. 2, pp.1301–1309.
5.    R. M. Balajee, K. Venkatesh. A Survey on Machine Learning Algorithms and finding the best out there for the considered seven Medical Data Sets Scenario. Research J. Pharm. and Tech. 2019; 12(6):3059-3062. doi: 10.5958/0974-360X.2019.00518.3
6.    Megha Mishra, Vishnu Kumar Mishra, H.R. Sharma. An Impact of Machine Learning with Lexcio-Syntatics Features of Question Classification. Research J. Engineering and Tech. 3(4): Oct-Dec. 2012 page 327-331.
7.    Carvalho, T.P.; Soares, F.A.A.M.N.; Vita, R.; da Francisco, P.R.; Basto, J.P.; Alcalá, S.G.S. A systematic literature review of machine learning methods applied to predictive maintenance. Comput. Ind. Eng. 2019, 1, 1–12.
8.    N. Soni, E. Sharma, N. Singh and A. Kapoor, "Artificial Intelligence in Business: From Research and Innovation to Market Deployment", Procedia Computer Science, vol. 167, pp. 2200-2210, 2020. Available: 10.1016/j.procs.2020.03.272
9.    Faggella, "How to Apply Machine Learning to Business Problems", Emerj, 2020. [Online]. Available: https://emerj.com/ai-executive-guides/how-to-apply-machine-learning-to-business-problems
10.    C. Services, C. Tool, P. Courage, O. Offerings and D. Platform, "Real-World Benefits of Machine Learning in Healthcare", Health Catalyst, 2020. [Online]. Available: https://www.healthcatalyst.com/clinical-applications-of-machine-learning-in-healthcare.
11.    Sindhu J, Renee Namratha. Impact of Artificial Intelligence in chosen Indian Commercial Bank –A Cost Benefit Analysis. Asian Journal of Management. 2019; 10(4):377-384. doi: 10.5958/2321-5763.2019.00057. X
12.    F. Weber and R. Schütte, "A Domain-Oriented Analysis of the Impact of Machine Learning—The Case of Retailing", Big Data and Cognitive Computing, vol. 3, no. 1, p. 11, 2019. Available: 10.3390/bdcc3010011.
13.    Meenakshi K, Safa M, Karthick T, Sivaranjani N. A Novel Study of Machine Learning Algorithms for Classifying Health Care Data. Research J. Pharm. and Tech. 2017; 10(5): 1429-1432. doi: 10.5958/0974-360X.2017.00253.0
14.    L. M˘aru¸ster, "A machine learning approach to understand business processes", CIP-DATA LIBRARY TECHNISCHE UNIVERSITEIT EINDHOVEN, 2003, ISBN 90-386-1688-0 NUR 982.
15.    Anitha A, Revathi SV, Jeevanantham S, Eliza Godwin E. Intrusion Detection System based on Artificial Intelligence. Int. J. Tech. 2017; 7(1): 20-24. doi: 10.5958/2231-3915.2017.00005.0
16.    Machine Learning for Business", Medium, 2020. [Online]. Available: https://medium.com/mindsdb/machine-learning-for-business-c24cb198dbb5.
17.    Wuest, T.; Weimer, D.; Irgens, C.; Thoben, K.D. Machine learning in manufacturing: Advantages, challenges, and applications. Prod. Manuf. Res. 2016, 4, 23–45.
18.    S. Sasireka. Comparative analysis on video retrieval technique using machine learning. Research J. Science and Tech. 2019; 11(2):148-154. doi: 10.5958/2349-2988.2019.00022.6.
19.    Rashmi R., Nirmal Raj VK. A Study on the Implementation and the Impact of Artificial Intelligence in Banking Processes. Asian Journal of Management. 2021; 12(1):47-54. doi: 10.5958/2321-5763.2021.00008.1.

Recomonded Articles:

Author(s): Divya Bharti

DOI: 10.5958/2349-2988.2019.00018.4         Access: Open Access Read More

Author(s): Minakshi M. Sonawane, Bharti W. Gawali, Ramesh R. Manza, Sudhir Mendhekar

DOI: 10.52711/2349-2988.2022.00024         Access: Open Access Read More

Author(s): Neha Bhateja, Nishu Sethi, Shivangi Kaushal

DOI: 10.52711/2349-2988.2021.00033         Access: Open Access Read More

Author(s): Praveen Tahilani, Hemant Swami, Gaurav Goyanar, Shivani Tiwari

DOI: 10.52711/2349-2988.2022.00030         Access: Open Access Read More

Author(s): Bhushan S. Mahajan, Bhupendra Sing P. Mahale, Amol R. Pawar, Vikas V. Patil, Pankaj S. Patil, Jayesh Songire

DOI: 10.52711/2349-2988.2024.00020         Access: Closed Access Read More

Author(s): Asane Varad Arun, Pangavhane Namrata Balasaheb, Jori Vikas Babasaheb, Jadhav Dipak Kailas, Kale Rushikesh Adinath, Nalawade Dipak Dadasaheb

DOI: 10.52711/2349-2988.2024.00034         Access: Closed Access Read More

Research Journal of Science and Technology (RJST) is an international, peer-reviewed journal, devoted to science and technology...... Read more >>>

RNI: Not Available                     
DOI: 10.5958/2349-2988 


Recent Articles




Tags