Hiring is broken. Recruiters are drowning in resumes, losing time, and missing great talent.
Resume Screening is not just another Python project — it's a bold step toward transforming how we discover potential. Built with clarity, speed, and purpose, this tool uses intelligent automation to read resumes, understand them, and match them to the right opportunities.
This isn’t about filtering resumes. This is about finding the right people — faster, smarter, and without bias.
- Extracts key resume insights with NLP — clean, structured, and fast.
- Matches candidates to job descriptions using semantic similarity.
- Learns and improves with machine learning algorithms.
- Runs on Streamlit, for instant, interactive, and beautiful UI.
| Technology | Purpose |
|---|---|
| Python | Core logic and data processing |
| NLP (spaCy, TF-IDF) | Understands human language |
| ML (scikit-learn) | Makes intelligent predictions |
| Streamlit | Interactive user interface |
| Pandas, NumPy | Data handling and transformation |
Resume-Screening/
├── DataSet/ # Sample resumes and job data
├── Model/ # ML models and logic
├── WebSite/ # Streamlit app code
├── requirements.txt
└── README.md
# Step 1: Clone the repository
git clone https://github.com/AdilShamim8/Resume-Screening.git
# Step 2: Navigate to the folder
cd Resume-Screening
# Step 3: Install dependencies
pip install -r requirements.txt
# Step 4: Launch the app
streamlit run WebSite/app.pyWhether you're a coder, designer, or just someone passionate about solving real-world problems — your ideas are welcome. Fork it, build it, improve it.
MIT License — because great tools should be free to build, break, and better.
- Add resume ranking
- Integrate LinkedIn profile parsing
- Build a full recruiter dashboard
- Add feedback-based ML training
This is more than code. It’s a tool for every company that believes hiring the right people is the most important thing they do.
Let’s reinvent recruitment — one resume at a time.