Resume Screening using Machine Learning and Python

AI/ML enthusiast | B.E. in AI/ML @ CMRIT | Building innovative solutions with Python, React, TensorFlow, and AWS. Passionate about resume screening, web apps, and ethical tech.

A machine learning project for ResumeScreening.

A machine learning project that predicts salaries based on candidate profiles and evaluates resumes using NLP techniques. It combines regression models and resume scoring logic to assist in data-driven recruitment decisions.

🎯 HireLens – An AI-powered resume screening and feedback platform for both jobseekers and recruiters. Get resume scores, improvement tips, and smart candidate ranking — all in one place.

AI-powered Resume Screening and Ranking System using Streamlit and NLP. This project is made by me in AICTE internship program by Edunet under the guidence of Saumya Chaudhari.

This project analyzes and preprocess the resumes data (consist of 2K+ instances) applying Natural Language Processing (NLP). It also involves the classification applying a variety of Machine Learning (ML) techniques.

AI Hiring Recommendation System is an ML-powered tool that analyzes job descriptions and candidate profiles to generate match scores. Using NLP, vectorization, and weighted similarity, it ranks candidates based on skills and relevance, helping streamline recruitment and improve shortlisting accuracy.

This is a resume matcher application that allows users to upload resumes and filter them based on must-know and better-to-know skills. It processes resumes, extracts skills, and generates a report based on the best-matched candidates.

This ATS AI tool score and suggestions to your resume.

Resume Screening usinf NLP and ML Technique

Embark on a machine learning journey with Python to streamline the resume screening process. This project aims to efficiently select the most suitable candidates for a job posting among numerous applicants.