I built a RAG-Based AI Teaching Assistant that retrieves information from video-based learning content and generates context-aware responses using an llama3.2 LLM. I converted lectures into timestamped transcripts with Whisper and used embeddings and semantic retrieval to find relevant content.
For my NSL-KDD intrusion detection project, I compared Logistic Regression, Random Forest, and Decision Tree models, evaluated class imbalance with macro F1-score, and developed a Streamlit application to present model evaluations and findings.
