  We evaluate the following Machine Learning techniques for Green Energy (Wind,
Solar) Prediction: Bayesian Inference, Neural Networks, Support Vector
Machines, Clustering techniques (PCA). Our objective is to predict green energy
using weather forecasts, predict deviations from forecast green energy, find
correlation amongst different weather parameters and green energy availability,
recover lost or missing energy (/ weather) data. We use historical weather data
and weather forecasts for the same.
