Group Project to predict hourly energy consumption and renewable energy production using historical weather and calendar data. Compares machine learning models constructed using time series regression, artificial neural networks, ensemble methods (gradient boosting, AdaBoost, random forests), and SVM.
Repository contains:
- Code that I contributed, written in Jupyter and R Markdown
- FinalPaper.pdf - Written Report
- FinalPresentation.pdf - Presentation file