JennyTan5522/NLP-Resume-Parsing
An automated Hybrid Resume NER based on Rule-Based model, Machine Learning Model, and Transformer model
This project helps HR professionals and recruiters automate the tedious process of manually sifting through resumes. It takes raw resumes as input and automatically extracts key information like names, contact details, skills, and work experience. The output is structured data that enables quick searching, summarization, and ranking of candidates, streamlining the initial screening process.
No commits in the last 6 months.
Use this if you need to efficiently process a large volume of resumes and automatically extract candidate details to accelerate your hiring workflow.
Not ideal if you only handle a very small number of resumes or prefer a completely manual review process without any automation.
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Last pushed
Aug 05, 2024
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