Publication Type : Book Chapter
Publisher : IEEE
Source : 2023 5th International Conference on Inventive Research in Computing Applications (ICIRCA)
Url : https://ieeexplore.ieee.org/abstract/document/10220707
Campus : Amritapuri
School : School of Computing
Year : 2023
Abstract : Salary prediction encompasses the intricate process of extrapolating or forecasting the anticipated remuneration or compensation for a specific job posting or occupational position. This research elucidates the intricate task of salary prediction for job postings by leveraging the amalgamation of cutting-edge web scraping techniques and sophisticated machine learning algorithms. An extensive corpus of job postings from diverse online platforms is meticulously amassed through meticulous data acquisition encompassing web scraping methodologies and comprehensive surveys. The resultant model, meticulously developed using Python and seamlessly integrated within the highly versatile Flask web framework, culminates in a practical, deployable solution.
Cite this Research Publication : Sukumar, J. G., Mohith Sai Ram Reddy, Nikhileswar Sambangi, S. Abhishek, and T. Anjali. "Enhancing salary projections: a supervised machine learning approach with flask deployment." In 2023 5th International Conference on Inventive Research in Computing Applications (ICIRCA), pp. 693-700. IEEE, 2023.