contents to fight overfitting stacking recurrent layers using bidirectional rnns going even further wrapping up sequence processing with convnets understanding convolution for sequence data pooling for sequence data implementing convnet combining cnns and rnns to process long sequences wrapping up summary deep-learning best practices advanced going beyond the sequential modelthe keras functional api introduction to the functional api multi-input models multi-output models directed acyclic graphs of layers layer weight sharing models as layers wrapping up inspecting and monitoring deep-learning models using keras callbacks and tensorboard using callbacks to act on model during training introduction to tensorboardthe tensorflow visualization framework wrapping up getting the most out of your models advanced architecture patterns hyperparameter optimization model ensembling wrapping up summary deep learning generative text generation with lstm brief history of generative recurrent networks how do you generate sequence data the importance of the sampling strategy implementing character-level lstm text generation wrapping up deepdream implementing deepdream in keras neural style transfer wrapping up the content loss the style loss neural style transfer in keras wrapping up licensed to