An intelligent web application that analyzes resumes against job descriptions using machine learning to provide match scores, personalized suggestions, and video recommendations for career improvement.
🎯 Try it now: https://resume-analyser-cm.streamlit.app/
- 📊 Resume-Job Matching: Calculate similarity scores using TF-IDF vectorization and cosine similarity
- 📄 PDF Processing: Extract and analyze text content from PDF resumes
- 🎯 Smart Suggestions: Generate personalized improvement recommendations
- 🎥 Video Recommendations: Curated video content for skill enhancement
- 📱 Responsive Design: Mobile-first design that works on all devices
- Python 3.7 or higher
- pip package manager
- Clone the repository:
git clone https://github.com/SpicychieF05/Ai-resume-analyser.git
cd Ai-resume-analyser- Install dependencies:
pip install -r requirements.txt- Run the application:
streamlit run app.pyThe application will open in your browser at http://localhost:8501
- streamlit - Web application framework
- PyPDF2 - PDF text extraction
- scikit-learn - Machine learning algorithms
- pandas - Data manipulation
- numpy - Numerical computing
- Upload Resume: Select a PDF file containing your resume
- Enter Job Description: Paste the job description you want to match against
- Get Analysis: View your match score and personalized suggestions
- Watch Videos: Access recommended improvement videos
- Improve: Update your resume based on feedback
We welcome contributions! Please follow these steps:
- Fork the repository
- Create a feature branch (
git checkout -b feature/AmazingFeature) - Commit your changes (
git commit -m 'Add some AmazingFeature') - Push to the branch (
git push origin feature/AmazingFeature) - Open a Pull Request
This project is licensed under the MIT License.
Chirantan Mallick
- GitHub: @SpicychieF05
- LinkedIn: chirantan-mallick
- Twitter: @chirantan_mallick
- Portfolio: linktr.ee/chirantan_mallick
- Streamlit: For the amazing web app framework
- scikit-learn: For powerful machine learning tools
- PyPDF2: For reliable PDF processing
Made with ❤️ by Chirantan Mallick
If this project helped you, please consider giving it a ⭐!