The Resume Screening project leverages Natural Language Processing (NLP) techniques to automate the process of screening resumes. This tool is designed to assist HR professionals and recruiters in quickly identifying qualified candidates by analyzing and extracting key information from resumes.

The motivation behind creating this project was to streamline the hiring process by reducing the time and effort required to screen resumes manually. With the growing number of job applicants, this tool aims to enhance efficiency and ensure that the best candidates are shortlisted based on their skills and qualifications.

The project utilizes the following technologies and libraries:

• Programming Languages: Python
• Libraries and Frameworks:
  • 🤗 Transformers: Hugging Face Transformers for NLP model implementation.
  • 📊 Data Manipulation & Analysis: Pandas, NumPy
  • 🔍 Text Preprocessing: NLTK, SpaCy
  • 📝 Machine Learning: scikit-learn
  • 🌐 Web Development: Flask (for a simple web interface)

• 🔄 Automated Resume Screening: Automatically screens and ranks resumes based on predefined criteria.
• 🧠 NLP Techniques: Utilizes NLP for extracting key information such as skills, experience, and education.
• 📝 Customizable Criteria: Allows recruiters to define specific criteria for shortlisting candidates.
• 🌐 Web Interface: Provides a user-friendly web interface for easy interaction.
• 📈 Efficiency: Significantly reduces the time needed for the initial resume screening process.

To install and run the project, follow these steps:

1. Clone the repository:

   git clone https://github.com/Sanskruti0404/Resume-Screening-Model.git
   cd Resume-Screening-Model

2. Install the required libraries:

   pip install transformers pandas numpy flask nltk spacy scikit-learn

3. Run the Flask app:

   python app.py

4. Access the web interface: Open your browser and navigate to http://127.0.0.1:5000/.

1. Open the web interface: Navigate to the provided URL.
2. Submit a resume: Copy and paste the resume text into the provided input field.
3. Screen the resume: Click on the 'Screen' button to analyze the resume.
4. View the score: The screening score will be displayed on the screen, indicating the resume's suitability based on the predefined criteria.

• Email: [email protected]
• LinkedIn: Sanskruti Giri

I'm always open to discussing new projects, ideas, or opportunities. Feel free to reach out!

Thank you for visiting my project. Let's create something amazing together! ✨