|
|
--- |
|
|
language: en |
|
|
license: mit |
|
|
pipeline_tag: text-classification |
|
|
tags: |
|
|
- resume |
|
|
- ats |
|
|
- pii |
|
|
- nlp |
|
|
- huggingface |
|
|
--- |
|
|
|
|
|
# 🤖 Resume PII Masking & ATS Optimizer |
|
|
|
|
|
A professional-grade NLP pipeline to automatically **detect and mask Personally Identifiable Information (PII)** in resumes and **evaluate resume quality based on Applicant Tracking System (ATS) scoring**. Built using the Hugging Face Transformers ecosystem and fine-tuned with custom data, this project simulates real-world applications of Natural Language Processing in HR tech and recruitment automation systems. |
|
|
|
|
|
--- |
|
|
|
|
|
## Key Features |
|
|
|
|
|
| Feature | Description | |
|
|
|-------------------------------|----------------------------------------------------------------------------| |
|
|
| PII Masking | Detects and masks names, emails, phone numbers, and addresses using NER. | |
|
|
| Resume Parsing | Handles large resumes (up to 2000+ words) with tokenizer support. | |
|
|
| ATS Resume Optimization | Scores resumes based on keyword density, formatting, and clarity. | |
|
|
| Job Description Matching | Optional feature to match resumes with specific job descriptions. | |
|
|
| Hugging Face Integration | Fine-tune and deploy models directly on Hugging Face Hub. | |
|
|
| Modular Architecture | Well-organized, scalable, and production-ready codebase. | |
|
|
|
|
|
--- |
|
|
|
|
|
## 📁 Folder Structure |
|
|
|
|
|
```bash |
|
|
resume_ats_project/ |
|
|
├── data/ # Contains resume samples and PII-labeled training data |
|
|
│ ├── resumes.json |
|
|
│ └── pii_train.json |
|
|
├── models/ # Directory to save fine-tuned models |
|
|
│ └── ats_model/ |
|
|
├── resume_parser.py # Tokenization, segmentation, and formatting |
|
|
├── pii_trainer.py # Script to fine-tune NER model |
|
|
├── optimizer.py # ATS scoring logic |
|
|
├── infer.py # Combines parsing, masking, and optimization |
|
|
├── app.py # (Optional) Flask or Gradio interface |
|
|
├── requirements.txt |
|
|
└── README.md |
|
|
|
|
|
|
|
|
--- |
|
|
Installation |
|
|
git clone https://github.com/your-username/resume-ats-optimizer.git |
|
|
cd resume_ats_optimizer |
|
|
pip install -r requirements.txt |
|
|
|
|
|
--- |
|
|
Real-World Applications |
|
|
This project mimics systems used by: |
|
|
LinkedIn Talent Solutions (Resume scoring + redaction) |
|
|
Amazon HR Automation (Internal resume screening tools) |
|
|
Google Cloud AutoML NER for internal document pipelines |
|
|
Infosys & TCS resume filtering portals |
|
|
|
|
|
--- |
|
|
You can adapt it to: |
|
|
Job matching portals |
|
|
Candidate anonymization systems |
|
|
Large-scale recruitment automation tools |
|
|
|
|
|
--- |
|
|
License |
|
|
Licensed under the MIT License. |
|
|
|
|
|
--- |
|
|
Author |
|
|
Karthikeyan M C |
|
|
karthikeyanmc1925@example.com |
|
|
|
