devshah7543 / AI_Project

AI_Project

LinkedIn 2.0

TEAM 13 : Shreedhar Bhatt (18BCP150D), Dev Shah (18BCP019), Devanshi Shah (18BCP023), Jahnavi Shah (18BCP041), Parn Desai (18BCP149D)
Recruiters and HR teams in companies have a tough time scanning thousands of qualified resumes. Either they need many people to do this or they miss out on qualified candidates. This is a waste of time, money and productivity for the company. To solve this, our resume parser application can take in millions of resumes, parse the needed fields and categorise them. This resume parser uses the popular python library - Tesseract for OCR and text classifications. We use cosine similarity to determine the similarity of the uploaded job description and the resumes.

Installation

Use the package manager pip to install the following:

pip install flask
pip install re
pip install nltk
pip install sklearn

Steps to execute project

• Download zip file or clone the project.
  
• Execute installations.
  
• Open command prompt of that resume_rating directory.
  
• Execute command :

python resume_rating_main.py

• A prompt will be generated stating "Starting development server at http://127.0.0.1:8000/" (Depends on your localhost)
  
• Paste the link to any web browser.

Screenshots

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.