Overview

Aims to develop a resume parser using computer vision techniques to analyze and extract information from resumes or CVs. The goal is to convert unstructured resume data into a structured format, such as XML and JSON, making it machine-readable. By doing so, the project intends to facilitate the efficient management of electronic resumes for recruiters, enabling them to extract essential information like contact details, work experience, educational background, and skill sets in an intelligent manner.

Tech Stack
  • Pytorch
  • Spacy Ner
  • Transformers
  • Python
  • Flair
  • NLTK

 

Challenges
  • Analyse resume or CV data
  • Extract it into machine-readable output such as XML and JSON.
  • Converts an unstructured form of resume data into a structured format

 

Outcome
  • Development of a resume parser
  • Enhanced recruiter efficiency
  • Improved candidate screening

 

Conclusion

The project successfully addressed the need for efficient resume management by developing a resume parser using computer vision techniques. By converting unstructured resume data into a structured format, recruiters can now process resumes more effectively, leading to improved candidate screening and selection processes. The system’s ability to extract essential information such as contact details, work experience, education, and skills enhances the overall recruitment workflow.

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