Resume Parser and Score Analyzer

A machine learning and cloud-based application for parsing resumes and analyzing their relevance to job requirements.

Project Overview

This application provides the following features:

• Resume parsing from various file formats (PDF, DOCX, TXT)
• Text extraction and processing using NLP techniques
• Skills and experience identification
• Resume scoring based on job requirements
• Cloud-based architecture for scalability
• User-friendly interface for uploading resumes and viewing results

Project Structure

Cloud-ML/
├── app/                    # Main application code
│   ├── api/                # API endpoints
│   ├── models/             # ML models
│   ├── parsers/            # Resume parsing modules
│   ├── scoring/            # Resume scoring logic
│   └── utils/              # Utility functions
├── cloud/                  # Cloud infrastructure code
├── data/                   # Data storage
│   ├── processed/          # Processed resume data
│   ├── raw/                # Raw resume files
│   └── training/           # Training data for ML models
├── frontend/              # User interface
├── notebooks/             # Jupyter notebooks for experimentation
├── tests/                 # Test cases
└── requirements.txt       # Project dependencies

Technologies Used

• Programming Languages: Python, JavaScript
• ML/NLP Libraries: spaCy, scikit-learn, TensorFlow/PyTorch
• Cloud Services: AWS (S3, Lambda, EC2) or GCP (Cloud Storage, Cloud Functions)
• Web Framework: Flask/FastAPI (backend), React (frontend)
• Document Processing: PyPDF2, python-docx

Getting Started

1. Clone the repository
2. Install dependencies: pip install -r requirements.txt
3. Set up cloud credentials
4. Run the application: python app/main.py

License

MIT