Added test for new trainer methods. Back to documentation style more in line with some popular packages like pytorch

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

Added Test. Ignored a number of typing related errors after updated to latest version of numpy (need to look into this. Ready to move on with notebooks

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

decoupled the model from the training process via the introduciton of a Trainer class. All seems easier now. Need to adjust all documentation. Also added a few losses and an R2 metric, as well as the possibiliy of customising virually every single component of the model

Adjusted documentation and examples. Refactored the LRHistory callback and fix bug in the History callback. Added multiple tests and increased code coverage to 94 per cent

fixed a bug related to the focal loss. Remove activations before the losses in the fit method in WideDeep. Sigmoid and logSoftmax happen within the loss. Added activations in the train and eval step and in the predict method

refined the documentation for the WarmUp class. Fix an issue regarding to the model type. Added a test for the warm up functionalities