AI system that detects fraudulent job postings using Machine Learning and Natural Language Processing.
Fake job postings are common on online job portals. This project builds an AI system that analyzes job descriptions and predicts whether the posting is real or fraudulent.
The system also highlights suspicious words and shows a Fraud Risk Meter to explain the prediction.
- NLP text preprocessing
- TF-IDF feature engineering
- Logistic Regression classification
- Fraud risk visualization
- Suspicious keyword highlighting
- Interactive web application
Dataset ↓ Text Cleaning ↓ TF-IDF Vectorization ↓ Logistic Regression Model ↓ Prediction ↓ Fraud Risk Meter + Explainability
Accuracy: 96%
The model handles imbalanced datasets and focuses on detecting fraudulent postings effectively.
- Python
- Scikit-learn
- Pandas
- NLTK
- Streamlit
fake-job-detector-ai │ ├── app.py ├── fake_job_model.pkl ├── tfidf_vectorizer.pkl ├── requirements.txt ├── README.md └── images ├── app_interface.jpg └── prediction_result.jpg
Install dependencies:
pip install -r requirements.txt
Run the web app:
streamlit run app.py
- Deploy the application online
- Improve explainable AI visualization
- Add deep learning NLP models
Abhay AI & Machine Learning Enthusiast