Finished documentation. Adjusted Notebooks. Renamed WarmUp class to what it really is, FineTune. Alias the corresponding parameters so that the user can use both, finetune and alias params. Modified a few defaults

adjust README. Adjust 2 first notebooks and write a new one (02_2). Fixed some examples of usage. Added FullEmbeddingDropout to TabTransformer. Encapsulate alias in Classes in loss_and_obj_alias module and change some minor style text

redo all docs to match pytorch theme. Adjust all documentation to the new code structure. Remove partial imports from...everywhere. Updated examples

Added comment for Mac users regarding the dataloaders not running in parallel for the latest torch version or python versions >= 3.8. Also, upgraded sub-version of the package to 0.4.7

updated docs so they are consistent with new functionalities. Updated logo. Updated README and fix a typo in setup.py

Finished implementation of DeepDenseResnet. Adapated DeepDense code for consistency (simply renamed 'embed_p' to 'embed_dropout'). Adapted docs and README. Included unit test for DeepDenseResnet.

Changed loss value printed on the screen for regression. From RMSE to MSE. Adjusted documentation. Also changed unit test for callbacks to the new Linear-Embedding implementation, which implied incresing delta for early stopping

Changed README, wide_deep.py, docs, and examples according to the new metrics. Only thing left is adjust the notebooks

updated examples and docs to show the use of the warm parameter. Updated README to include Acknowledgments