Overview
This research-style project models electricity demand patterns using historical demand signals and calendar features. The goal is to communicate uncertainty clearly, not simply produce a single forecast line.
Method
The notebook compares baseline moving averages, Prophet-style decompositions, and gradient boosting regressors with lag features.
Outcome
The strongest insight was that simple baselines are valuable. A model earns its complexity only when it improves accuracy and interpretability.