Keyword extraction from job descriptions to get better insights about the key skills using TF-IDF

"Job Recommendation System with Streamlit: Upload CVs, extract skills, and get job recommendations using TF-IDF and Jooble API. Recruiters can paste job descriptions to find the best-matched CVs with similarity scoring. Features PDF parsing,NLP for skill extraction, real-time job fetch, and downloadable reports.

Built an AI-powered resume analysis platform that compares resumes against job descriptions using NLP and LLM-based skill extraction to identify missing skills and generate improvement suggestions.

Group project to build an NLP-based HR tool in Python that parses resumes, extracts skills, and matches them with job descriptions to rank candidates. I handled data preprocessing using TF-IDF, BERT, and SpaCy for text cleaning, tokenization, and feature extraction.

AI Resume–JD Matcher is a smart web application that analyzes how well a candidate’s resume matches a given job description. It uses NLP techniques like TF-IDF and cosine similarity along with skill extraction to generate a match score, highlight matched and missing skills, and provide improvement feedback.

NLP-based resume and job description matcher using TF-IDF, cosine similarity, and spaCy-based skill extraction.

AI-powered resume screening system using NLP, skill extraction, and FastAPI to match resumes with job descriptions.

An NLP-powered system that matches resumes to job descriptions using semantic similarity and skill extraction techniques.

NLP-based system to analyze resumes and match them with job descriptions using skill extraction and similarity scoring.

An AI-powered resume screening tool that compares resumes with job descriptions using NLP-based skill extraction to compute match percentage and identify missing skills.

Description : Developed a Flask-based web application that matches candidate skills with job requirements using NLP for skill extraction and comparison. Tech stack : Python, Flask, SpaCy, NLP, HTML/CSS/JS.

AI-powered resume and job description matching system using NLP, Sentence Transformers, spaCy skill extraction, FAISS vector search, and Streamlit dashboard.

An end-to-end NLP pipeline that ranks resumes against a job description using semantic embeddings (sentence-transformers) and skill extraction

AI-powered resume screening system that analyzes uploaded resumes and matches them with job descriptions using NLP-based skill extraction and similarity scoring.

An intelligent, AI-powered platform that analyzes resumes against job descriptions using advanced NLP to provide match scoring, skill extraction, and actionable feedback.

AI/ML-based system that matches resumes with job descriptions using NLP, semantic similarity, and skill extraction, served via FastAPI with a JavaScript frontend.

NLP-driven system for skill extraction and gap analysis between candidate profiles and job descriptions, using semantic embeddings, structured scoring, and an interactive Streamlit frontend.

AI-powered Resume Screening System built with Python and Streamlit that matches candidate resumes with job descriptions using NLP-based skill extraction and similarity scoring.

This repository studies the application of BERT-based models for skill classification from job description texts, aiming to support automatic skill extraction and labor market analysis using NLP techniques.

AI-powered Resume Analyzer that matches resumes with job descriptions using NLP. Upload a resume and get skill extraction, job matching, and compatibility scores based on a real job dataset. Built using Python, Flask, and Machine Learning techniques.

A machine learning-based resume analyzer that evaluates job seeker's resumes against job descriptions to assess job fit. Built using Spark ML for model training, NLP for skill extraction, and Streamlit for an interactive UI.

An AI-powered job portal built with the MERN stack and a Python-based NLP microservice to intelligently match candidate resumes with job descriptions using BERT embeddings, skill extraction, and hybrid scoring techniques.

A robust ATS Resume Analyzer using a Hybrid NLP approach (SBERT + TF-IDF) to score resumes against job descriptions, featuring semantic matching, synonym-aware skill extraction, and report generation.

: 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.

A simple NLP-powered tool that compares a resume to a job description and highlights matched and missing keywords. Built using Python and spaCy for skill extraction and match scoring.

Developed an AI-driven recruitment automation system using Java & Spring Boot to analyze resumes and match skills with job descriptions. Implemented NLP-based skill extraction to calculate job-fit scores and identify missing skill gaps. Automated candidate ranking and shortlisting to enhance hiring speed and decision accuracy.

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.

An NLP-powered system that matches CVs with job descriptions using spaCy NER for skill extraction and BERT embeddings for similarity scoring, with a Streamlit interface for interactive ranking and visualization.

NLP-powered resume parsing system using spaCy, transformers, and rule-based extraction. Automatically extracts skills, experience, education, contact info from resumes. Features skill matching against job descriptions, similarity scoring, and candidate ranking. Includes interactive dashboard for bulk resume analysis.

An Applicant Tracking System (ATS) that analyzes resumes against job descriptions using explainable NLP and machine learning techniques, featuring TF-IDF-based matching, rule-based skill extraction, resume classification, and Dockerized deployment.