Automation Of Skill Extraction And Feedback Recommender System Using Machine Learning

The project’s main goal is to employ machine learning to create an automated method for skill extraction and feedback recommendation. The proposed system extract pertinent talents from online portfolios, social media profiles and resumes using Natural Language Processing (NLP). Candidates are then categorized using machine learning algorithms according to their projects, experience, and skill sets. Additionally, the system has a feedback recommender that helps candidates develop and match job needs by giving them tailored comments. By automating these procedures, the system streamlines talent acquisition and candidate evaluation while increasing recruiting efficiency, lowering bias, and enabling data-driven decision-making for recruiters.