n sequence generation tasks, what is the primary input to an RNN at each time step?Previous outputCurrent weightPrevious errorCurrent inputNone of the given options

Which layer type is commonly used in RNNs for sequence-to-sequence tasks?Question 31Answera.Hidden layerb.Attention layerc.Input layerd.Output layer

Recurrent Artificial Neural NetworksRecurrent Artificial Neural Networks (RNNs) are a type of neural network architecture that is designed to handle sequential data by introducing connections between units in the network that form directed cycles. This cyclic structure allows information to persist over time and enables the network to exhibit dynamic temporal behavior.In contrast to feedforward neural networks, where information flows in one direction from input to output, RNNs have connections that loop back on themselves, allowing them to maintain an internal state or memory of previous inputs. This makes them well-suited for tasks that involve sequential data or time series, such as natural language processing, speech recognition, and time series prediction. The basic unit of an RNN is called a recurrent neuron or a recurrent unit.

Which problem arises when training RNNs on long sequences?All of the given optionsUnderfittingVanishing or exploding gradientsOverfittingHigh bias

When using RNNs for music generation, what does each neuron in the output layer typically represent?A specific instrumentA possible note or rest in the musical vocabularyA frequency bandA note in the C major scaleA time step in the generated sequence

Recurrent Neural Network (RNN)