https://github.com/jayasai-gorre/resume-matcher
Resume Matcher is a Flask-based web app that compares job descriptions with uploaded resumes using NLP (TF-IDF and Cosine Similarity) to find the top matches. Upload multiple resumes and instantly get the best-fit candidates.
https://github.com/jayasai-gorre/resume-matcher
flask nlp-machine-learning
Last synced: 2 months ago
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Resume Matcher is a Flask-based web app that compares job descriptions with uploaded resumes using NLP (TF-IDF and Cosine Similarity) to find the top matches. Upload multiple resumes and instantly get the best-fit candidates.
- Host: GitHub
- URL: https://github.com/jayasai-gorre/resume-matcher
- Owner: jayasai-gorre
- Created: 2025-04-22T10:19:06.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-04-22T11:01:43.000Z (about 1 year ago)
- Last Synced: 2025-04-24T00:58:23.581Z (about 1 year ago)
- Topics: flask, nlp-machine-learning
- Language: Python
- Homepage: https://resume-matcher-6ovr.onrender.com/
- Size: 2.51 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Resume Matcher 🔍📝
A simple web application to match job descriptions with resumes using NLP (TF-IDF and Cosine Similarity). Upload multiple resumes and get the top matching ones based on the job description provided.
🌐 **Live Demo**: [Visit on Render](https://resume-matcher-6ovr.onrender.com/)
---
## 🚀 Features
- Upload multiple resumes in PDF, DOCX, or TXT format.
- Paste a job description.
- Get top 3 matching resumes with similarity scores.
- Built using Flask + Bootstrap.
- Responsive design with background image.
- Simple UI for real-world utility.
---
## 🛠 Tech Stack
- **Backend**: Python, Flask
- **Frontend**: HTML, CSS, Bootstrap
- **NLP**: Scikit-learn (TF-IDF + Cosine Similarity)
- **Hosting**: Render
---
## 📦 Installation (Local)
1. **Clone the repo**
```bash
git clone https://github.com/your-username/resume-matcher.git
cd resume-matcher
2. **Create virtual environment**
```bash
python -m venv myenv
source myenv/bin/activate # On Mac/Linux
myenv\Scripts\activate # On Windows
3. **Install dependencies**
```bash
pip install -r requirements.txt
4. **Run the app**
```bash
python main.py