Resume Screening Using NLP

Project Overview

This project leverages Natural Language Processing (NLP) to automate and optimize the process of screening resumes. By analyzing the text content of resumes, the model can extract key information, assess suitability for specific roles, and streamline the recruitment process.

Features

• Extracts structured data from resumes.
• Analyzes resumes for keyword relevance and job fit.
• Provides scoring mechanisms for shortlisting candidates.
• Designed for integration into end-to-end recruitment systems.

Installation

1. Clone this repository:

   git clone https://github.com/Durgesh5863/Resume-Screening-Using-NLP.git

2. Navigate to the project directory:

cd resume-screening-nlp

3. Install the required dependencies:

pip install -r requirements.txt

Usage

1. Place resumes in the media folder
2. Run the notebook file to process the resume
3. View the results in the media directory.

Dataset

The dataset used for this project includes anonymized resumes and job descriptions. Ensure compliance with privacy regulations when using real data.

Technologies Used

• Python
• NLP Libraries (SpaCy, NLTK, etc.)
• Pandas for data handling
• Jupyter Notebook for development and visualization

Contribution

Contributions are welcome! Please fork the repository and create a pull request.

License

This project is licensed under the MIT License.

Contact

For questions or collaborations, please reach out to: Durgesh Babu P

Email: [email protected]