This project aims to predict the electric load consumed by housing structures in the city Austin, Texas. The data spans 2 years and contains weather and time related variables.
Two modeling methods were used to make predictions: a pure Gaussian Process regression model (GP.ipynb) and then a Hidden Markov Model where a unique Gaussian Process regression model was built for each hidden state (HMM_GP.ipynb).