Energy Demand Prediction

<p><strong>Energy Demand Prediction</strong></p><p>This workflow forecasts hourly energy demand by aligning hourly timestamps, generating lag features and training an LSTM deep neural network. It includes:</p><ul><li><p>Data ingestion of historical energy consumption data</p></li><li><p>Timestamp alignment, missing value handling, and generation of lagged features as predictors</p></li><li><p>Training and application of a Keras-based LSTM deep neural network to forecast energy demand per hour</p><ul><li><p>Make sure to select the proper Conda environment for Keras under "Preferences &gt; Python Deep Learning". For more info and installation guidance, check the pertinent docs.</p></li></ul></li><li><p>Comparison of actual vs. predicted values via line plots and scoring metrics.</p></li></ul>