Case studyData Science / ML· Private project
Predictive ML Application
A Data Science project taken from raw data to a deployed application: problem framing, data preparation, modelling, and a usable interface.
01 — Problem
Predict a key quantity ahead of time so decisions can be planned instead of reacted to.
02 — Data
Historical records cleaned, joined and validated. Missing values and leakage handled explicitly before any modelling.
03 — Modeling
Baseline first, then tree-based models with cross-validation and interpretable feature importance.
04 — Application
A web interface where users load new data, get predictions and see which factors drove them.
05 — Deployment
Packaged and deployed so the model can be retrained and updated without rebuilding the application.