Applications of RNNs

So far, we have only talked about one-to-one-mapped RNNs, where the current output depends on the current input as well as the previously observed history of inputs. This means that there’s an output for the sequence of previously observed inputs and the current input. However, in the real world, there can be situations where there is only one output for a sequence of inputs, a sequence of outputs for a single input, and a sequence of outputs for a sequence of inputs where the sequence sizes are different. In this lesson, we’ll look at the four settings of RNN models and the applications they would be used in.

• One-to-one RNNs

• One-to-many RNNs

• Many-to-one RNNs ...