AI-powered Resume Screening System that analyzes and ranks resumes based on similarity to a job description using NLP and TF-IDF. Built with Python, Scikit-learn, and Streamlit, it extracts text from PDF/DOCX files and calculates cosine similarity to help recruiters shortlist candidates efficiently.

An automated Resume Screening and Ranking System using NLP and Machine Learning. Extracts text from PDFs/DOCX, classifies candidates using SVM, and ranks them against job descriptions via Cosine Similarity. Built with Python, Flask, and Scikit-Learn.

NLP-powered resume screening app — parses PDFs, ranks candidates by JD match using TF-IDF + cosine similarity, detects skill gaps, scores resumes. Built with Python + Streamlit + Django.

Intelligent talent screening tool using Machine Learning and NLP. Automatically analyzes resumes, extracts key information, scores candidates (0-100), and generates actionable recommendations. Built with Python - no external ML libraries required.

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Typically, large companies do not have enough time to open each CV, so they use machine learning algorithms for the Resume Screening task.I will take you through a Machine Learning NLP project on Resume Screening with Python programming language.

AI-powered Resume Screening and Ranking System using Python, NLP, and scikit-learn. Features data cleaning, feature extraction, and cosine similarity for efficient candidate ranking. Deployed with Streamlit Cloud.

An intelligent resume screening system that automates candidate shortlisting using Natural Language Processing (NLP). Built with Python, Streamlit, and scikit-learn, this project parses resumes, matches them with job descriptions, and ranks candidates based on relevance scores.

Automated Resume Screening and Candidate Ranking System using NLP and Machine Learning. This project analyzes resumes, extracts skills, and ranks candidates based on job requirements using TF-IDF and similarity scoring. Built with Python, Flask, and a modern interactive UI.

https://smart-resume-analyzer-gqstm9vovcrqdmxndvdr7s.streamlit.app/ AI-powered solution for resume screening and employee sentiment analysis. Uses NLP and Gemini AI to match resumes with job descriptions and predict attrition risk from employee feedback. Built with Python, scikit-learn, and Google AI Studio.

An automated resume screening system that parses PDF resumes, extracts key information, and ranks candidates based on job-specific criteria — similar to how modern ATS platforms operate. Built using Python, Tesseract OCR, NLP pipelines, and rule-based scoring to evaluate skills, experience, and relevance with high accuracy.

Developed a web-based resume parser application using Python with a Flask-based web interface and FastAPI for backend APIs. The system extracts structured candidate data from PDF/DOCX/JPG/PNG resumes using NLP techniques. Parsed data is validated and stored for further filtering and ranking, enabling efficient res screening.

AI Resume Screening & Ranking System 🚀 A Streamlit-based web app that uses NLP and Machine Learning to analyze and rank resumes based on job descriptions. Features PDF uploads, TF-IDF vectorization, Cosine Similarity for ranking, and detailed analytics. Built with Python, NLTK, scikit-learn, and PyPDF2.

A Python tool that reads and analyzes PDF resumes using keyword matching and NLP across 20+ skill areas. It predicts the best-fit job role, scores skills, and generates CSV reports with visual charts. Used PyPDF2, pandas, matplotlib, and tqdm to enable batch processing and clear, data-driven insights for resume screening.

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Resume-Screening-using-NLP-with-python

Build a Powerful Resume Screening App with Python | Resume Analyser Application using NLP Python

Resume Screening App With Python and Machine Learning or a Resume Analyser Application using NLP Python.

Created a resume Screening app using python implemented with NLP, machine learning and streamlit.

Powerful Resume Screening Application with Python & NLP This project demonstrates a robust Resume Screening Application built using Python and Natural Language Processing (NLP). Designed to automate and streamline the initial resume screening process, this application efficiently categorizes submitted resumes into relevant job profiles.

Powerful Resume Screening Application with Python & NLP This project demonstrates a robust Resume Screening Application built using Python and Natural Language Processing (NLP). Designed to automate and streamline the initial resume screening process, this application efficiently categorizes submitted resumes into relevant job profiles.

AI-based Resume Screening system that ranks resumes based on job descriptions using NLP (TF-IDF & Cosine Similarity). Built with Python & Streamlit

AI-powered Resume Screening Tool using NLP and Machine Learning (TF-IDF + Cosine Similarity) built with Python and Streamlit.

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.

AI-powered resume screening application that compares resumes with job descriptions using NLP, weighted skill matching, and TF-IDF similarity. Built with Python and Streamlit.

An AI-powered resume screening app that compares resumes to job descriptions using keyword extraction, TF-IDF scoring, and NLP. Built with Python and Streamlit.

An AI-powered resume screening system that automatically classifies resumes into job roles using machine learning and NLP, built with Python, scikit-learn, and Streamlit.

AI-driven tool for automating resume screening and skill-based candidate assessment using NLP and ML, built with Python and Streamlit.

End-to-end AI-powered resume screening system that analyzes resumes using NLP, matches candidates with job descriptions, scores resumes, and provides skill and course recommendations using Python and machine learning.