Skip to content

AI-powered tool to detect fraudulent job listings using NLP and machine learning. Built to enhance job seeker safety by identifying scams in real time, installation and setup guide given.

Notifications You must be signed in to change notification settings

smirk-dev/Spot-The-Scam-AI

Repository files navigation

🕵️‍♂️ Spot the Scam – Job Fraud Detection App

A machine learning-powered web app that detects whether a job posting is real or fake. Developed to help job seekers avoid online employment scams using natural language processing and supervised learning.


🚀 Live Demo

🔗 Hosted App: https://spothescamai.streamlit.app


🎥 Demo Video

📺 Presentation Link: https://www.youtube.com/your-video-link


🧠 Project Overview

Online job scams are rising rapidly, luring victims through fake offers and fraudulent listings. This app uses a trained machine learning model to classify job descriptions as legitimate or fraudulent, helping users make safer career decisions.


⚙️ Key Features & Technologies Used

  • 🔍 Predicts if a job post is fake or real
  • 🧠 ML model trained using Logistic Regression
  • 📋 Text preprocessing (stopwords, TF-IDF, etc.)
  • 🌐 Streamlit-based interactive frontend
  • 🧪 Model trained on real job post dataset
  • 📈 F1-Score: 0.88

🛠️ Technologies

-pandas -scikit-learn -streamlit -matplotlib -seaborn -plotly -joblib -Pillow -wordcloud -numpy -requests -shap


📁 Dataset & Model File

Due to file size, the trained model and original dataset are hosted externally.

📥 Download Link: https://drive.google.com/your-dataset-and-model-link

After downloading:

  • Place model.pkl in the models/ folder
  • Place the dataset (optional) in the data/ folder

🧪 Setup Instructions (Run Locally)

  1. Clone the repository:

    git clone https://github.com/your-username/spot-the-scam.git
    cd spot-the-scam
  2. (Optional) Create a virtual environment:

    python -m venv venv
    source venv/bin/activate       # On Windows: venv\Scripts\activate
  3. Install dependencies:

    pip install -r requirements.txt
  4. Download model file from Google Drive and place it in the models/ folder.

  5. Run the app:

    streamlit run app/app.py

📊 Model Performance

Metric Value
F1 Score 0.88
Accuracy 89.3%
Precision 0.87
Recall 0.89

🙋 Team Members

  • Suryansh MishraLead Developer & Data Scientist

🔗 Other Links


📂 Directory Structure

spot_the_scam_project/
│
├── app/
│   └── app.py
│
├── models/
│   └── model.pkl
│
├── data/
│   └── [not included – download from Drive]
│
└── README.md

About

AI-powered tool to detect fraudulent job listings using NLP and machine learning. Built to enhance job seeker safety by identifying scams in real time, installation and setup guide given.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published