Use MLBlocks for methods backend

[micahjsmith]

Currently, ATM defines learning methods (classification only) in json files within the repo. The MLBlocks/MLPrimitives projects provide similar functionality, but include many more methods, including neural networks, gradient boosted machines, and regression models (#72). We should explore using these projects as the backend for learning methods.

[micahjsmith]

Here are some thoughts on implementation:

• For each method in atm/methods/*.json, find a corresponding primitive in HDI-Project/MLPrimitives/mlblocks_primitives, such as RandomForestClassifier https://github.com/HDI-Project/MLPrimitives/blob/master/mlblocks_primitives/sklearn.ensemble.RandomForestClassifier.json
• Replace atm/methods/ dir with atm.constants.primitives or similar, a list of strings identifying MLPrimitives
• Use MLBlocks to make a pipeline: https://github.com/HDI-Project/ATM/blob/master/atm/model.py#L95

Ultimately, we want people to be able to include/upload their own primitives for use with MLBlocks.