Project · P-09
ForgeQB
An adaptive quizbowl study app with 500+ users, recommending from 160,000+ questions clustered into micro-categories.
- Lead 4-dev team building an adaptive quizbowl study app (500+ users) across Electron, FastAPI, and PostgreSQL stack.
- Engineered NLP ingestion, topic clustering and production epsilon-greedy softmax recommender (160,000+ questions).
- Prototyped RL recommender (DQN) against production softmax system using simulated student across varied reward structures.
Nearest neighbors · any layercosine distance in the full space