overview
an ml regression pipeline that predicts s&p 500 trends from historical price data and feature-engineered technical indicators. the random forest model hits 60% accuracy on the test set.
stack
a fastapi backend serves real-time predictions at 10+ requests per minute with sub-200ms response time. the whole stack is containerized with docker and deploys to render through a ci/cd pipeline that runs automated tests on every push.
