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resume-matcher

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CV Embed is an AI resume analyzer that matches candidates with job descriptions using SBERT/GloVe/Doc2Vec models. Calculates compatibility scores, suggests top job matches, and generates real opportunities. Supports PDF/DOCX uploads with Flask backend and Gemini AI integration.

  • Updated Jul 26, 2025
  • Python

This project aims to make the process of matching resumes with a particular job description much faster. Simply enter the required job-description and all the resumes that need to be filtered and run the script to find the top scorer as well as the 'n' best matching resumes! Built using Python, Hugging Face and Scikit-Learn.

  • Updated Mar 6, 2025
  • Python

This project aims to make the process of matching resumes with a particular job description much faster. Simply enter the required job-description and all the resumes that need to be filtered and run the script to find the top scorer as well as the 'n' best matching resumes! Built using Python, Hugging Face and Scikit-Learn.

  • Updated Mar 6, 2025
  • Python

AI Resume Matcher is an intelligent, local-first resume screening system powered by the Mistral 7B Instruct LLM. It takes a job description and multiple PDF resumes, compares each candidate’s experience, skills, and background, and generates a match percentage with a detailed reasoning report — all saved as Word documents.

  • Updated Jul 20, 2025
  • Python

Resume Matcher is a web app that analyzes resumes against a job description using AI. It extracts content from uploaded resumes and evaluates them based on skills, experience, and fit. The system uses Google's Gemini 2.0 model through LangChain for accurate matching and scoring. Users receive a clear match score and explanation for each candidate.

  • Updated Apr 26, 2025
  • Python

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