Fake Ad Detection

System Architecture

Overview

NLP fraud identification system classifying 50,000+ online advertisements. Ensemble approach combining LSTM, SVM, Doc2Vec, and TF-IDF features achieves 94% classification accuracy with 40% faster inference compared to baseline models. Deployed as a FastAPI microservice with real-time scoring.

Highlights

• 94% classification accuracy
• 50,000+ ads classified
• 40% faster inference vs baseline