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Implement Dataset and Corpus data loaders. (#535)

This PR implements a significant change in the way yellowbrick handles datasets, moving them from data that can be downloaded and loaded using example code to prime time members of the library that can be loaded into pandas data frames and series or into well-structured numpy arrays with correct data types. 

We have completely overhauled dataset management using the yellowbrick-datasets repository as our data management tool. Data is still stored on S3 but contains .csv.gz and meta.json files for loading into pandas if it's installed or .npz files for loading into valid numpy arrays. New `Dataset` and `Corpus` manage access to the data, downloading it if it's not already on disk and providing access to the contents in the source directory. We maintain our security checking with sha256 hashes and a new manifest.json method. 

Fixes #416

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