ML system that predicts student backlog risk from attendance, marks, assignments, and study hours using Random Forest classification.

• Random Forest model for risk prediction & classification (Low / High)
• Flask backend with SQLite for user and prediction data
• Responsive frontend in HTML and CSS
• Full data preprocessing & model training in Python

AI-powered tool that scrapes career pages, embeds job data, and crafts personalized cold emails using LLMs and RAG.

• Extracts job details from career pages with web scraping
• Vector embeddings + RAG for relevant portfolio matching
• Streamlit interface for end-to-end generation