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Machine learning practices in accounting and auditing

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Chetanpal Singh 1, *, Rahul Thakkar 2, Rashikala Weerawarna 1 and Vimal B Patel 3

1 Faculty of business, design and it, Holmesglen Institute Chadstone Campus Melbourne Australia.
2 Faculty of ICT, Victorian Institute of Technology (VIT), Melbourne Australia.
3 College of Agriculture, Navsari Agricultural University, Waghai, Gujarat, India.

Review Article
 
International Journal of Science and Research Archive, 2023, 10(01), 131–162.
Article DOI: 10.30574/ijsra.2023.10.1.0720
DOI url: https://doi.org/10.30574/ijsra.2023.10.1.0720

Received on 24 July 2023; revised on 03 September 2023; accepted on 06 September 2023

In the current technological era, Machine Learning applications are becoming popular every day. This research paper provides information about the effectiveness of the ML technique in accounting as well as the auditing process. To get proper results, different ML libraries are utilized, concluding seaborn, matplotlib, NumPy and so on. In the introduction section, the research purpose and this research objectives have been developed, through which the entire research process will be developed. “Logistic Regression Machine Learning Model” is built. Literary sources have been analyzed in the literature review section, through which it can be easy to gain different perceptions based on the research context. The effectiveness of different types of machine learning algorithms in accounting and auditing has been evaluated properly. To develop a knowledge level, it is important to increase proper attention, and this research paper will provide proper information based on ML effectiveness.

Machine Learning; Algorithm; Accounting; Auditing; Artificial neural network

https://ijsra.co.in/sites/default/files/fulltext_pdf/IJSRA-2023-0720.pdf

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Chetanpal Singh, Rahul Thakkar, Rashikala Weerawarna and Vimal B Patel. Machine learning practices in accounting and auditing. International Journal of Science and Research Archive, 2023, 10(01), 131–162. Article DOI: https://doi.org/10.30574/ijsra.2023.10.1.0720

Copyright © 2023 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0

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