https://github.com/arpan132002/fake-job-post-detection-nlp

This project focuses on detecting fake job postings using Natural Language Processing (NLP) techniques.
https://github.com/arpan132002/fake-job-post-detection-nlp

deep-learning machine-learning nlp

Last synced: about 1 month ago
JSON representation

This project focuses on detecting fake job postings using Natural Language Processing (NLP) techniques.

• Host: GitHub
• URL: https://github.com/arpan132002/fake-job-post-detection-nlp
• Owner: arpan132002
• Created: 2024-08-05T10:30:41.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2024-08-05T12:21:14.000Z (5 months ago)
• Last Synced: 2024-08-05T14:12:57.570Z (5 months ago)
• Topics: deep-learning, machine-learning, nlp
• Language: Jupyter Notebook
• Homepage:
• Size: 687 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# Fake-Job-Post-Detection-NLP

## Overview

This project focuses on detecting fake job postings using Natural Language Processing (NLP) techniques. The primary goal is to build a model that can identify fraudulent job listings, helping users to avoid scams and ensuring the authenticity of job posts.

## Features

- **Data Preprocessing**: Cleaning and preparing the dataset for analysis.

- **Text Vectorization**: Converting text data into numerical format using techniques like TF-IDF.

- **Modeling**: Using Linear Regression for classification tasks.

- **Evaluation**: Assessing the model's performance using appropriate metrics.

## Dataset

The dataset contains various features related to job postings, such as job descriptions, titles, locations, company names, and more. The target variable indicates whether a job post is real or fake.