Intelligent Resume Screening System that compares resumes with job descriptions using NLP, TF-IDF, cosine similarity, and skill-based scoring.
Recruiters often receive hundreds of resumes for a single job opening.
Manually checking every resume is time-consuming and inefficient.
This project automates the initial resume screening process by analyzing a candidate’s resume against a Job Description (JD) and generating an overall match score.
The system reads PDF resumes, preprocesses text, compares content using Machine Learning techniques, extracts technical skills, and provides matched / missing skills analysis.
- Automate resume screening process
- Compare resume with job description
- Detect relevant technical skills
- Reduce recruiter effort
- Learn NLP and Machine Learning practically
- Build a real-world Python project
Extracts text from PDF resumes using PyPDF2.
Performs:
- Lowercase conversion
- URL removal
- Symbol removal
- Extra space removal
- Stopword removal
Uses:
- TF-IDF Vectorization
- Cosine Similarity
to compare resume text with Job Description.
Detects skills such as:
- Python
- Java
- SQL
- C#.Net
- Backend
- Automation
- Git
- GitHub
Displays:
- Resume Skills
- Job Skills
- Matched Skills
- Missing Skills
Calculates final score using:
Final Score = (40% Text Similarity) + (60% Skill Match)
| Technology | Purpose |
|---|---|
| Python | Main programming language |
| PyPDF2 | PDF text extraction |
| NLTK | Stopword removal |
| Scikit-learn | TF-IDF + cosine similarity |
| Regex | Text cleaning |
| GitHub | Version control |
AI-Resume-Screener-Using-Python/
│── ResumeScreener.py
│── requirements.txt
│── README.md
│── RESUMES/sample_resume.pdf
Step 1: Clone Repository git clone https://github.com/PankajHarabhare09/AI-Resume-Screener-Using-Python.git
cd AI-Resume-Screener-Using-Python