Guide to Custom Recurrent Modeling in Keras

The initial set of layers for recurrent neural operations universally begins with LSTM, GRU and RNN. But with an increase in the complexity of the task, we should use more complex models. That said, before moving directly to different and relatively complex models like attention or transformers, we should first ask a simple question -- can we still do something quickly with the basic recurrent layers? In this article, I will focus on the same philosophy that -- we should first exhaust the simple solutions before going for the more complex ones. In the next sections, we will explore the same old set of recurrent layers (albeit with some interesting arrangements) to get better inference on the data.