A project leveraging LSTM and XGBoost to analyze and predict energy usage, identify inefficiencies, and optimize costs across buildings, providing actionable insights for energy management and savings.
exploratory-data-analysis data-cleaning decision-support model-evaluation time-series-forecasting cost-savings time-series-modeling energy-efficiency-analysis energy-optimization-recommendations weather-impact-analysis
-
Updated
Dec 28, 2024 - Jupyter Notebook