AI Resume Analyzer

This study explores the development of an AI Resume Analyzer, a tool designed to transform how resumes are evaluated by leveraging Natural Language Processing (NLP) and machine learning techniques. Despite the growing need for streamlined and unbiased resume analysis, many existing solutions lack personalized recommendations and actionable insights. The AI Resume Analyzer addresses this gap by automating resume parsing, extracting essential details such as names, emails, and skills, and providing an evaluation score out of 10. Additionally, it offers constructive feedback and resource suggestions, including curated YouTube videos to help applicants enhance their resumes. The research focuses on building a user-friendly interface using Streamlit, integrating Python modules such as pandas, pyresparser, and pdfminer3 for parsing and analysis, and employing Plotly for data visualization. A database system powered by MySQL ensures efficient data management and retrieval. Findings demonstrate that the AI Resume Analyzer significantly reduces manual effort while improving the accuracy and consistency of resume evaluations. The system achieves an extraction accuracy of 85-92% and a resume-job matching accuracy of 80-88%, with a processing time of 2-3 seconds per resume. Future research should focus on refining the analysis algorithms and expanding the system to accommodate multilingual resumes and domain-specific requirements.