Traditionally, pinpointing the best possible model for a given prediction problem requires optimizing an entire parameter space—and even taking this step involves choosing between a number of different methodologies. Auto Tune Models (ATM), our cloud-based modeling system, provides an easier, faster way to narrow down to the best choice. ATM performs bandit-based and Gaussian process learning to decide among methodologies, as well as to pinpoint which parameters and hyperparameters should be used for modeling. The result is a vastly more efficient end-to-end process.