dffml

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As part of the second stage of the GSOC AutoML project as defined in #968, this is a preliminary iteration of the AutoML model. The idea is to allow users to provide a dataset and list of models they wish to train, and DFFML's integrated AutoML model will perform training/tuning/scoring to select the best model for the user, abstracting away much of the ML process into an easy-to-use API. The current iteration performs the training and scoring using default hyperparameters, so has not implemented tuning yet. Some discussion by the community will be needed to evaluate the best way for tuning to occur in the AutoML process. (should we have default hyperparameter search spaces for each model, or must it be user-defined?)