No description available

AI-powered resume–job matching platform that uses NLP (spaCy + TF-IDF) and advanced Data Structures (Trie + Graph) to match resumes to jobs, detect skill gaps, and generate dependency-ordered learning roadmaps.

AI-powered resume-to-job recommender system that extracts skills from resumes using spaCy + PDFMiner, applies semantic search with Transformers, and ranks matches with keyword heuristics. Includes an interactive Streamlit app with job title and location filters.

AI-powered ATS Resume Scorer built with Streamlit and spaCy. Upload your resume and a job description to get a match score, phrase-level insights, and improvement suggestions.

A Python-based application utilizing Natural Language Processing (NLP) to analyze and compare resumes against job descriptions. It extracts keywords, calculates semantic similarity scores, and evaluates how well a resume matches job requirements, leveraging spaCy and NLTK libraries.

A resume analysis tool that extracts skills, experience, and education from PDF resumes using NLP (spaCy) and matches them with job roles to provide smart suggestions and improvement tips. Built with Python and Streamlit, ideal for freshers and job seekers.

This repository contains a web application that uses Natural Language Processing (NLP) and machine learning to match resumes with job requirements. Built with Flask, Bootstrap, and spaCy, this tool streamlines the recruitment process by scoring candidates based on skillset match.

🤖 AI-powered resume analysis tool that matches your skills with job requirements using advanced NLP and machine learning. Upload your resume and job description to get instant feedback, skill gap analysis, and personalized improvement suggestions. Built with Flask, spaCy, Sentence Transformers, and deployed on Render.

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.

No description available

A resume-to-job matcher using spaCy embeddings and Streamlit

Resume to Job description matcher with NLP using spacy's EntityRuler

A Flask and spaCy application to intelligently match resumes with job descriptions

A Python app to match resumes with job descriptions using spacy and streamlit

AI-powered resume-job matcher using NLP and vector search (spaCy + Qdrant). Parses resumes, embeds text, and ranks candidates by semantic relevance to job descriptions.

NLP-powered resume screening tool that auto-matches candidates to job descriptions using spaCy · Python · Flask

Resume-to-job matcher built with spaCy, Scikit-learn & Streamlit. Extracts skills via NLP, scores job fit with ML, and shows gap analysis.

1. AI-Powered Resume Screener + Job Match System ML/DS Part: Use NLP (spaCy, HuggingFace, or BERT) to extract skills, experience, and education from resumes. Match them against job descriptions ...

AI-powered resume ranking system using spaCy NLP to match candidates with job requirements and generate detailed skill gap analyses

AI-powered resume screener built with Streamlit and spaCy. Upload your resume and job description to get match scores, keyword analysis, and smart suggestions.

Resume-to-Job Matcher is an AI-driven tool that helps recruiters and job seekers by matching resumes with job descriptions. It extracts skills from resumes using NLP (spaCy, NLTK) and compares them with job requirements. Using embeddings from Hugging Face Transformers and cosine similarity, it calculates a match score.

AI-powered Resume Matcher & Text Intelligence tool leveraging NLP (Spacy, NLTK, Scikit-Learn) to extract, analyze, and rank resumes against job descriptions. Unlock recruiter efficiency with smart parsing, semantic search & insightful candidate-job fit scoring.

AI-powered Resume Analyzer leveraging Streamlit, spaCy, and scikit-learn to extract skills, analyze resumes, match job descriptions, and provide ATS-friendly suggestions for improvement.

Automated resume screening using Natural Language Processing techniques. Extracted and classified resume data to identify key skills, job roles, and match scores with job descriptions. Tools used: Python, Spacy, NLTK, Sklearn, Streamlit.

Built with Python, Streamlit, and spaCy NLP, this app compares a resume (PDF) to a job description, providing match percentage and improvement suggestions.

AI-Powered Resume Analyzer – Developed a Streamlit web app that uses BERT embeddings & cosine similarity to evaluate job-resume fit. Implemented NLP-based skill extraction (spaCy + keyword library) to highlight matched & missing skills, delivering job match scores and skill-gap analysis for recruiters.

Streamlit app that extracts keywords from PDF resumes and job descriptions using spaCy, then compares them to show keyword matches, and an overall score.

An AI-powered resume screening and ranking system built with Django, NLP (Spacy, Transformers), and Machine Learning. Automatically matches resumes to job descriptions based on skill relevance and experience.

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.

Automate resume evaluation using Python to match job requirements efficiently. Parse resumes with spaCy, match keywords TF-IDF, and rank candidates using scoring algorithms. Visualize results with Matplotlib. This saves time, reduces bias, and streamlines recruitment.