Predictive Insights: using Machine Learning to Determine Your Future Salary
M. Saraswathi1, J. Akhila2, K. Sireesha3
1Dr. M. Saraswathi, Assistant Professor, Department of Computer Science Engineering, Sri Chandrasekarendra Saraswathi Viswa Maha Vidyalaya, Enathur (Tamil Nadu), India.
2J. Akhila, B.E, 4th Year Student, Department of Computer Science Engineering, Sri Chandrasekarendra Saraswathi Viswa Maha Vidyalaya, Enathur (Tamil Nadu), India.
3K. Sireesha, B.E, 4th Year Student, Department of Computer Science Engineering, Sri Chandrasekarendra Saraswathi Viswa Maha Vidyalaya, Enathur (Tamil Nadu), India.
Manuscript received on 25 March 2023 | Revised Manuscript received on 05 April 2023 | Manuscript Accepted on 15 May 2023 | Manuscript published on 30 May 2023 | PP: 1-7 | Volume-13 Issue-2, May 2023 | Retrieval Number: 100.1/ijsce.B36050513223 | DOI: 10.35940/ijsce.B3605.0513223
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Abstract: Knowing one’s expected salary can be a crucial consideration when deciding whether to change careers or seek higher education in today’s fiercely competitive work market. Accurate salary forecasts provide valuable insights into the earning potential of various professions, as numerous students graduate each year and workers seek to transition into new sectors. To forecast a salary range, this paper proposes a computerised method that takes into account a person’s country of origin, level of education, years of experience, and area of specialisation. This type of system has obvious benefits, as it empowers individuals and groups to make informed decisions about job prospects, wage negotiations, and employee retention. The system’s data can be utilised by researchers, academic institutions, and policymakers to inform their evaluation of labour market trends and make informed decisions. The reliability and accuracy of the system’s data, the forecasting models employed, and the regularity of system maintenance and updates will all impact these factors. However, it is a promising area for further research and development due to the benefits of having a reliable technique for estimating salaries.
Keywords: Machine learning, Prediction, Regression, Supervised learning.
Scope of the Article: Machine learning