This tutorial will introduce how to leverage scikit-learn's powerful
histogram-based gradient boosted regression trees with various loss functions
(Least squares, Poisson and the pinball loss for quantile estimation) on a time
series forecasting problem. We will see how to leverage pandas to build lag and
windowing features and scikit-learn time-series cross-validation tools and other
model evaluation tools.