NLP · AI · Fraud Detection
Fake Ad Detection
NLP Fraud Classification System
PythonLSTMSVMDoc2VecTF-IDFscikit-learnFastAPI
System architecture
- Ad text50,000+ ads
- FeaturesTF-IDF · Doc2Vec
- LSTMAIsequence model
- SVMAIscikit-learn
- EnsembleAIcombined vote94% accuracy
- Scoring APIFastAPI microservice40% faster inference
Measured in production
94%Classification accuracy
Inference time vs baseline−40%
40% faster50,000+Ads classified
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.
Result
- 94% classification accuracy
- 50,000+ ads classified
- 40% faster inference vs baseline