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Code to parse information such as Name, Email, Phone Number, Skill sets and Qualification from a given resume.

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dhinu95/Resume-Parser-Using-NLP

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Resume-Parser-Using-NLP

Built Resume Parser using Natural Language Processing(NLP) in Python.

Intially check extension of file either .pdf or .docx. Convert pdf or docx file content into text. Then using NLP-Spacy,nltk,. libraries extract Name, Mobile number, Mail id, Qualification, Technical Skills from resume.

NLP Libraries used

1. spaCy

spaCy is a free, open-source library for advanced Natural Language Processing (NLP) in Python. spaCy is designed specifically for production use and helps you build applications that process and “understand” large volumes of text. It can be used to build information extraction or natural language understanding systems.

2. NLTK

The Natural Language Toolkit (NLTK) is a platform used for building Python programs that work with human language data for applying in statistical natural language processing (NLP). It contains text processing libraries for tokenization, parsing, classification, stemming, tagging and semantic reasoning.

.py files:

• Extract text: text.py
• Name: name.py
• Mobile Number: mbl_number.py
• Mail id: mail.py
• Qualification: qualification.py
• Technical Skills: skills.py

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Code to parse information such as Name, Email, Phone Number, Skill sets and Qualification from a given resume.