v0.3

Bridgescaler v0.3 has some major feature enhancements and bug fixes.

• DeepQuantileTransformer: Performs quantile transforms on multi-dimensional datasets where the last dimension is the variable (channels-last in deep learning library context).
• Distributed scalers: we have standard and min max scalers that can be applied on separate subsets of the data and then be combined in map-reduce fashion. They support both tabular and n-dimensional datasets, so you can use them for large datasets that don't fit in memory on a single node.

What's Changed

• GroupMinMaxScaler fixes by @djgagne in #3
• Deep Quantile Transformer by @djgagne in #6

Full Changelog: v0.2...v0.3