This project is an AI-based system that uses NLP and machine learning to analyze resumes and match them with job descriptions. It extracts skills, applies TF-IDF for feature representation, and uses multiple models for classification. The system generates a match score and highlights skill gaps through a Streamlit interface.

AI-powered web application that analyzes resumes against job descriptions to identify skill gaps and generate personalized learning recommendations. Built with a hybrid approach combining rule-based extraction and LLM-powered analysis, the system provides accurate skill matching, missing skill detection, and actionable career insights.

This project proposes an AI-based Resume Skill Extraction and Job Matching System that uses Natural Language Processing (NLP) to automate and improve the recruitment process. The system intelligently analyses resumes and job descriptions to extract relevant skills, qualifications, experience, and keywords.

🚀 Built an AI Resume + Job Matcher System Developed an intelligent web application that analyzes resumes and matches them with relevant job roles using AI-driven insights. 🔍 Key Features: • Resume parsing and skill extraction • AI-based resume scoring and feedback • Job role matching based on skills and experience • Skill gap analysis

: Resume Extraction & Skills Matching System — Built an AI-based web app to extract key details and skills from PDF resumes and match them against job descriptions using NLP and fuzzy matching. The system highlights matched and missing skills and provides suggestions to improve role suitability.

Resume Matching System An AI-powered application that analyzes and matches resumes with job descriptions using NLP and skill extraction. It ranks candidates based on matching percentage and provides career guidance for both selected and non-selected applicants.

Built an AI-based resume screening and job matching system using Java, Spring Boot, and Spring AI, improving match accuracy by 40%. •Automated resume parsing and skill extraction using LLM-based semantic analysis, reducing screening time by 50%. •Developed scalable REST APIs for resume upload and job recommendations using Spring MVC.

AI Hiring Platform | Python, FastAPI Developed an AI-based resume screening system using Python and FastAPI Implemented PDF resume parsing and skill extraction Built a job matching algorithm to calculate candidate suitability score Designed a recruiter dashboard using HTML and CSS

Developed an AI-driven resume ranking system leveraging TF-IDF vectorization and cosine similarity for semantic matching. Combined NLP-based similarity scoring with rule-based skill extraction to create a hybrid ranking model. Implemented weighted evaluation logic to improve candidate-job alignment accuracy.

Built an AI-based resume parsing and job matching system using NLP & ML • Implemented PDF resume ingestion, skill extraction, and similarity-based ranking • Deployed Flask REST application on cloud with real-time processing • Live Demo: https://your-app.onrender.com Tech: Python, NLP, Machine Learning, Flask, MongoDB, REST APIs, Git