v0.2.2: WandB, K-Fold cross validation, better tracking of measures, and many bugfixes.

Improvements

Added integration with Weights and Biases.
Added K-Fold cross validation.
Added 4 examples with their respective code and Jupyter Notebooks: Hyper-parameter optimization, K-Fold Cross Validation, MNIST, Titanic.
Greatly improved the measures tracked on the TensorBoard.
Added auto-detect function for field separator when reading CSVs.
Added CI tooling.
Class weights can be specified as a dictionary #615.
Removed deprecation warning from h5py.
Removed most deprecation warning from TensorFlow.
Bypass multiprocessing.Pool.map for faster execution.
Updated TensorFlow dependency to 1.15.2.
Various documentation improvements.

Bugfixes

Fix cudnn error on RTX GPUs.
Fix inverted confusion_matrix axis.
Fix #201: Removed whitespace as a separator option.
Fix #540: Fixed default text parameters for sampled loss.
Fix #541: Docker image improvements (removed libgmp and spacy model download).
Fix #554: Fix audio input test case in docker container.
Fix #570: Temporary dolution for in_memory flag usage in API.
Fix #574: Setting intra and inter op parallelism to 0 so that TF determine them automatically.
Fix #329 and #575: Fixed use of SavedModel and added an integration test.
Fix #609: When predicting, if a split is in the CSV, data is split correctly.
Fix #616: Change preprocessing in siamese network example.
Fix #620: Failure in unit tests for 1 vs all calibration plots.
Fix #632: Setting minimum version requirements for six.
Fix #636: CLI output table column ordering preserved when resuming.
Fix #641: Added multi-task learning section specifying the weight for each output feature in the User Guide.
Fix #642: Fixing horovod use when loading a model as initialization.

Contriburotrs

@jimthompson5802 @calz1 @pingsutw @vanpelt @carlogrisetti @anttisaukko @dsblank @borisdayma @flozi00 @jshah02