An explainable Python-based system that analyzes skill gaps between resumes and job descriptions using transparent text processing and deterministic logic.
Most resume screening tools rely on black-box AI models that provide little insight into why a candidate is a good or bad match.
This project focuses on explainability, correctness, and interview-readiness.
- Resume & Job Description text normalization
- Rule-based skill extraction
- Skill gap analysis (matched vs missing skills)
- Transparent scoring logic
- Actionable improvement suggestions
- Python
- Regex-based text processing
- Rule-based NLP (no black-box ML)
🚧 In progress — developed day-by-day with a strong focus on fundamentals and design clarity.