Data Modeling for Recurrent Neural Networks (RNN)

In the last article, we discussed the Data and Task jar for Sequence labeling problems. In this article, we touch upon the data modeling aspect for Sequence classification and sequence labeling problems

Data Modeling

A model is an approximation of the true relationship that exists between the input and the output. And the only difference in modeling for Sequence Learning Problems in comparison with other problems is that there is not a single input, but instead “a series of inputs”

In a sequence classification problem, the output depends on the entire sequence for example for a sequence sentiment analysis problem, the output depends on all the words in the sequence and not just the first word or the last word

So, the objective is to come up with a function such that the final output is a function of all the inputs and a recurrent neural network essentially serves this purpose

In a Fully Connected Neural Network (FCNN) the output depends on a single input something like the below

And “y_hat” is computed using the below equations (complete details are covered in this article)

The model’s equation for Recurrent Neural Network (RNN) is very similar to the equation in FCNN, the only change in the case of…