A web-based application that leverages AI to screen and rank resumes based on job descriptions, making your hiring process efficient and effective.
For a detailed overview of the project, you can refer to the project Document: AI-powered Resume Screening and Ranking System - Project Document
- Resume Screening: Automatically screen resumes based on the provided job description.
- Candidate Ranking: Rank candidates using AI-powered algorithms for better hiring decisions.
- PDF Support: Upload resumes in PDF format for seamless processing.
Frontend
- Streamlit (for building interactive web applications)
Backend
- Python (for server-side operations)
- PyPDF2 (for extracting text from PDF files)
- scikit-learn (for text processing and similarity calculations)
github.com/codewithshek/AI-powered-Resume-Screening-and-Ranking-System/
├── Readme.md
├── AI-powered-Resume-Screening-and-Ranking-System-PPT.pdf
└── Main.py
- Clone the Repository
git clone https://github.com/codewithshek/AI-powered-Resume-Screening-and-Ranking-System.git
cd AI-powered-Resume-Screening-and-Ranking-System
- Install Dependencies
pip install -r requirements.txt
- Run the Application
streamlit run Main.py
- Access the Application
Open your browser and navigate to the generated custom URL like http://localhost:8501/ to start using the AI-powered resume screening tool.
- extract_text_from_pdf(file): Extracts text from a given PDF file.
- rank_resumes(job_description, resumes): Ranks resumes based on the provided job description using cosine similarity.
✅ Implement support for additional file formats (e.g., DOCX).
✅ Add advanced natural language processing (NLP) techniques for better resume analysis.
✅ Develop a mobile application for on-the-go resume screening and ranking.
Feel free to fork and submit pull requests. Any contributions are welcome!
Made with ❤️ by D ABHISHEK YADAV as part of AICTE- Internship on AI: Transformative Learning with TechSaksham – A joint CSR initiative of Microsoft & SAP, focusing on AI Technologies