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A Study of Application of No Regret Learning Algorithm for Development of a Career Counselling Software

Tamada Kiran Deepthi, Makineedi Triveni, Setti Venkata Kalyani, Lakkavarapu Hemanth, Manas Kumar Yogi

Abstract


This paper explores the application of “no regret learning algorithms” in the development of a career counselling software, aimed at providing individuals with personalized and data-driven career guidance. By harnessing the power of machine learning methods, this groundbreaking approach provides a flexible and responsive system designed to aid users in making well-informed choices regarding their career trajectories. The software incorporates user profiling, reward modelling, continuous feedback mechanisms, and ethical considerations to ensure relevant and unbiased career recommendations. This technology, by minimizing the feeling of missed opportunities and continually improving career choices, holds great promise in the realm of career counselling. It has the potential to enhance the decision-making process, ultimately leading to greater long-term career satisfaction and success for individuals.


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