AI Resume Analyzer: Smart Resume Evaluation and Enhancement

This paper presents an AI-driven resume analyzer designed to streamline and enhance the job candidate assessment process. The system utilizes Natural Language Processing (NLP) techniques and machine learning algorithms to process and evaluate resumes efficiently. By extracting key information, calculating an ATS compatibility score, identifying grammar errors, and providing improvement suggestions, the analyzer aims to assist both job seekers and recruiters optimize the resume screening process. The platform also evaluates resumes against job-specific requirements and offers curated resources, to help users develop relevant skills and stay competitive in the job market. By automating the resume review process, the project enables job seekers to enhance their profiles, increasing their chances of success in today's dynamic hiring environment. Designed with scalability, accuracy, and user-friendliness in mind, this application serves as a valuable tool for job seekers, recruiters, and educational institutions. The system is implemented using Python, FastAPI for the backend, and Streamlit for a user-friendly interface. KEYWORDS: AI Resume Analyzer, Natural Language Processing, Machine Learning, Resume Screening, Applicant Tracking Systems (ATS), TF-IDF, Fuzzy Matching, FastAPI, Streamlit.