CONCLUSION & FUTURE WORK

Developed an end-to-end ML pipeline for phishing URL detection with 96% F1 score

Implemented robust validation and drift detection to ensure model reliability

Established comprehensive MLOps practices with experiment tracking and CI/CD automation

Deployed containerized solution to AWS with real-time and batch prediction capabilities

Implement feature extraction from raw URLs to eliminate manual feature engineering

Incorporate deep learning models (LSTM/Transformers) for improved accuracy

Add A/B testing framework for production model updates and continuous improvement

Create browser extension for seamless end-user protection and feedback loop