I want to know if Deep learning can be used for Resume Parsing and scoring of the resume.

Currently what I am doing is extracting the text from pdf or image using OCR/tesseract and finding the features like Email, Mobile No, Skills, Tenure, No of Companies, Awards etc from the text. So I have close to 100 features which are important for scoring the resume.

Can we do similar thing using Deep learning and will the accuracy be better ? Any starting point/document/blog/github link which can help me get started on this.

I have gone through this link but this doesn't not have code to start with.


1 Answer 1


Resume parsing and scoring can be done by identifying relevant keyword in the text. NER (Named Entity Recognition) is a technique to identify relevant keywords in text. There are different framework available to work with NER and NLP as a whole. I will suggest you to look into spacy

to train a custom NER model.


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