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@article{180668,
        author = {Nikhil Kumar and Rahul Kumar},
        title = {Job Prediction Using Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {2108-2111},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180668},
        abstract = {The fast advancement of the worldwide 
work showcase has made a squeezing requirement for 
progressed frameworks to encourage proficient 
enlistment and career arranging. This ponder explores 
the utilize of machine learning procedures for work 
expectation, pointing to coordinate work searchers with 
appropriate parts by examining their abilities, 
capabilities, involvement, and inclinations. The 
technique envelops information pre-processing, 
highlight designing, and hyper- parameter optimization 
to make strides show exactness and unwavering quality. 
The framework not as it were upgrades the enrollment 
handle by minimizing bungles between candidates and 
managers but to give significant experiences for career 
direction. It powerfully adjusts to shifts in work 
advertise requests, advertising personalized proposals 
based on advancing industry necessities. Besides, the 
integration of prescient analytics guarantees that both 
work searchers and selection representatives can make 
educated, data-driven choices. This approach has the 
potential to revolutionize workforce administration, 
streamline contracting forms..},
        keywords = {Work Forecast, Machine Learning, Career  Arranging, Enrollment Optimization.},
        month = {June},
        }