All projects
Machine Learning
Stock Price Prediction Engine
Result
Low RMSE / MAE
Stack
PythonXGBoostNumPyMatplotlib
01 - The problem
Financial decision-making needed a quantitative forward view rather than backward-looking reporting alone.
02 - Approach
Engineered lagged and rolling features from historical price series, trained an XGBoost regressor, and evaluated it on held-out periods using RMSE and MAE to keep the error profile honest.
03 - Outcome
Achieved strong accuracy with low error metrics, giving a defensible input into financial analysis and scenario planning.