Projects

• Cleaned data, applied SMOTE, and trained a Gradient Boosting model to predict fraudulent vehicle claims (94% accuracy).
• Trained a CNN model using Keras for crack detection, achieving 87.4% validation accuracy based on All-CNN paper.
• Built a RAG framework with LangChain, Elasticsearch, OpenAI, FastAPI and deepeval implementing different retrieval methods.