I am trying to make a NN(probably with dense layers) to map a specific input to a specific output (or basically sequence2sequence). I want the model to learn the relation between the sequences and predict the output of any other input I give it.
I have 2 files - one with the inputs and another with all the corresponding outputs and would probably use a bunch of Dense Layers with word embeddings to vectorize it into higher dimensions. However, I cannot find any good resources out there for that.
Does anyone know how to accomplish such an NN? Which architectures are best for pattern matching? examples, links, and other resources would be very welcome. I was considering using RNN's but found them not very good in the pattern matching tasks so had ditched them. I would still consider them if someone can provide a plausible explanation...