🤖 AI Resume Analyzer

An intelligent resume analysis system powered by deep learning and natural language processing. Upload your resume, select a target job role, and get instant AI-powered insights including category classification, job match scoring, and skill extraction.

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✨ Features

• 🔍 Smart Resume Parsing - Extracts skills, email, and key information using NLP
• 🎯 AI Classification - BERT-based deep learning model categorizes resumes into 24 professional domains
• 📊 Job Matching - Semantic similarity analysis provides 0-100% compatibility scores
• 🎨 Modern UI - Beautiful, professional interface with glassmorphism design
• 🔗 REST API - JSON-based API for programmatic access

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🚀 Quick Start

1. Install Dependencies

pip install -r requirements.txt

2. Train the Model

python train_model.py

⏱️ Takes 30-60 minutes on CPU

3. Run the Application

python app.py

4. Open in Browser

http://localhost:5000

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📋 Requirements

• Python 3.7+
• 2GB free disk space
• Internet connection (for initial model downloads)

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🎯 How It Works

1. Upload Resume - Drag and drop or click to upload (TXT, PDF, DOC, DOCX)
2. Select Job Role - Choose target position from dropdown
3. Get Results - View category, match score, skills, and recommendations

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🧠 Technology Stack

• Backend: Flask, Python
• Deep Learning: PyTorch, BERT, Sentence-BERT
• NLP: NLTK, HuggingFace Transformers
• Data: Pandas, NumPy, Scikit-learn
• Frontend: HTML5, CSS3, JavaScript

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📊 Model Performance

• Classification Accuracy: 85-90%
• Categories: 24 professional domains
• Skills Detected: 50+ technical and soft skills
• Inference Time: 2-3 seconds per resume

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🎨 Screenshots

Home Page

Beautiful gradient background with glassmorphism effects and easy file upload.

Results Page

Comprehensive analysis with category, match score, skills, and actionable recommendations.

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📖 Documentation

For detailed documentation including architecture, API reference, and training process, see PROJECT_DOCUMENTATION.md.

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🔧 Configuration

Change Port

Edit app.py:

app.run(debug=True, port=5001)  # Change from 5000 to 5001

Adjust Training

Edit train_model.py:

classifier.train(
    csv_path='data/Resume.csv',
    epochs=3,        # Increase epochs
    batch_size=8,    # Increase if you have more RAM
    learning_rate=2e-5
)

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🐛 Troubleshooting

Model Not Found

python train_model.py

Out of Memory

Reduce batch size in train_model.py:

batch_size=2  # Instead of 4

Port Already in Use

Change port in app.py or kill existing process.

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📁 Project Structure

resume_project/
├── data/                    # Datasets
│   ├── Resume.csv          # Resume training data
│   └── job_title_des.csv   # Job descriptions
├── models/                  # Trained models (created after training)
├── modules/                 # Core modules
│   ├── parser.py           # Resume parsing
│   ├── classifier.py       # BERT classification
│   └── matcher.py          # Job matching
├── static/                  # CSS files
├── templates/               # HTML templates
├── app.py                   # Flask application
├── train_model.py          # Training script
└── requirements.txt        # Dependencies

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🎓 Categories

The system classifies resumes into 24 professional domains:

ACCOUNTANT, ADVOCATE, AGRICULTURE, APPAREL, ARTS, AUTOMOBILE, AVIATION, BANKING, BPO, BUSINESS-DEVELOPMENT, CHEF, CONSTRUCTION, CONSULTANT, DESIGNER, DIGITAL-MEDIA, ENGINEERING, FINANCE, FITNESS, HEALTHCARE, HR, INFORMATION-TECHNOLOGY, PUBLIC-RELATIONS, SALES, TEACHER

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🔗 API Usage

Endpoint

POST /api/analyze
Content-Type: application/json

Request

{
  "resume_text": "Your resume text here...",
  "job_description": "Job description here..."
}

Response

{
  "category": "INFORMATION-TECHNOLOGY",
  "match_score": 85.5,
  "skills": ["Python", "Machine Learning", "TensorFlow"],
  "email": "example@email.com"
}

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👥 Team

Developed By:

• Maitreya Pawar
• Prakasita Mohanty
• Nehal Garg
• Saniya Sawnt

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📄 License

This project is licensed under the MIT License.

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🙏 Acknowledgments

• BERT: Google's Bidirectional Encoder Representations from Transformers
• Sentence-BERT: Sentence embeddings using Siamese BERT networks
• HuggingFace: Transformers library and model hub
• NLTK: Natural Language Toolkit

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📞 Support

For issues, questions, or contributions, please refer to the PROJECT_DOCUMENTATION.md file.

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© 2024 AI Resume Analyzer - Powered by BERT, Sentence-BERT, and NLP