v0.3.2: New datasets, better processing of binary and numerical, minor fixes

Changelog

Additions

• Added feature identification logic (#957)
• Added Backend interface for abstracting DataFrame preprocessing steps (#1014)
• Add support for transforming numeric predictions that were normalized (#1015)
• Added Kaggle API integration and Titanic dataset (#1021)
• Add Korean translation for the README (#1022)
• Added cast_columns function to preprocessing and cast_column function to all feature mixin classes (#1027)
• Added custom encoder / decoder registration decorator (#1017)
• Add titles to Hyperopt Report visualization (#1026)
  -Added cast_columns function to preprocessing and cast_column function to all feature mixin classes (#1027)
• Added label-wise probability to binary feature predictions (#1033)
• Add support for num_layers in sequence generator decoder (#1050)
• Added Flickr8k dataset (#1053)
• Add support for transforming numeric predictions that were normalized (#1015)

Improvements

• Improved triggering of cache re-creation (now it depends also on changes in feature types)
• Improved legend and add tight_layout param to compare predictions plot (#1037)
• Improved postprocessing for binary features so prediction vocab matches inputs (#1038)
• Bump TensorFlow and tfa-nightly for 2.4.0 release (#1058)
• Updated Dockerfiles to TensorFlow 2.4.0 (#1059)

Bugfixes

• Fix missing yaml files for datasets in pip package
• Fix hdf5 preprocessing error
• Fix calculation of the metric score for hyperopt (#1031)
• Fix wrong argument in visualize.py from -f to -ofn (#1032)
• Fix fill NaN by adding selected conversion of columns to string when computing metadata (#1042)
• Fix: inconsistent seq length for probabilities (#1043)
• Fix issues with changes in xlrd package (#1056)