Bigml

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- Removing traces and refactoring Flatline interpreter invocation.
- Migrating tests to pytest.

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- Enabling local models to generate the transformations pipeline used in
training to be able to apply it locally to input data for predictions.
- Refactoring local models to bring the feature extraction capabilities to
the transformations pipeline.
- Rounding local numeric predictions and scores to 5 digits.
- Improving Pipelines and Image Processing documentation.

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- Fixing local batch_prediction method on DataFrames.
- Improving the training examples method in the Fields class to produce
examples of categorical field values following their original distribution.

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- Renaming Pipeline class to BMLPipeline and refactoring to allow scikit-learn
and Pandas pipelines to be also part of the Pipeline transformations.
- Adding several DataTransformers (BMLDataTransformer, SKDataTransformer and
DFDataTransformer) as wrappers for transformation generators.

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- Fixing dump methods for all local resources.
- Refactoring output options in batch_predict methods.
- Adding name and description to local resources.

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- Fixing locale check.
- Documenting the new ``.batch_predict`` method added to local models to
homogenize local batch predictions and accept Pandas' DataFrame as input.