About Dataset What's In The Deep-NLP Dataset? Sheet1.csv contains 80 user responses, in the responsetext column, to a therapy chatbot. Bot said: 'Describe a time when you have acted as a resource for someone else'. User responded. If a response is 'not flagged', the user can continue talking to the bot. If it is 'flagged', the user is referred to help. Sheet2.csv contains 125 resumes, in the resumetext column. Resumes were queried from Indeed.com with keyword 'data scientist', location 'Vermont'. If a resume is 'not flagged', the applicant can submit a modified resume version at a later date. If it is 'flagged', the applicant is invited to interview. What Do I Do With This? Classify new resumes/responses as flagged or not flagged. There are two sets of data here - resumes and responses. Split the data into a train set and a test set to test the accuracy of your classifier. Bonus points for using the same classifier for both problems.

curriculum vitae

Text Extraction from resume using LangExtract

Python project

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Simple Resume

Script to resume a text from a page or directly from a String using Python

ResumeTextValidator is an advanced document inspection tool designed to validate and analyze .docx resume files for formatting, character consistency, and placeholder content. It intelligently detects unusual symbols, unwanted phrases, and mixed Arabic-English text in professional documents.

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Latex Template for a clean resume

webapp summarizes text and creates presentations

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A fully-integrated into MTS True Tabs API on Flask with a model (NBC) that analyzes TF-iDF representation of the resume text and predicts whether it is substantive.

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A Simple pdf test parser (FronEnd)

A simple pdf text parser (BackEnd)

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