Category : AI-Powered Resume Matching System (CV Embed)

Client : My university Project

Description : CVEmbed is a sophisticated web application that leverages AI and Natural Language Processing (NLP) to help job seekers find the best-fitting roles. The system acts as an intelligent resume analyzer, matching candidates' resumes or CVs with job descriptions to calculate a compatibility score. The project's core is its semantic analysis engine, which uses advanced models to understand the meaning behind the text, going beyond simple keyword matching. The application provides users with a clear, step-by-step workflow, visual score visualizations, and direct suggestions for top-matching jobs and real opportunities. This project demonstrates a strong command of both front-end and back-end development, as well as complex AI model integration.

Technologies : HTML5, CSS3, JavaScript, Jinja2 Templating, Python 3.8+, Flask, RESTful APIs, Sentence Transformers (SBERT), Gensim (GloVe/Doc2Vec), NLTK (tokenization), PyPDF2, python-docx, Regex, Google Gemini Pro, Docker, Gunicorn, Nginx

Project URL : GitHub Repository

Project date : 2025/07/18