Recurrent Neural Networks are best suited for Text Processing. True or False?
Answers
Recurrent neural network (RNN) is a range of artificial neural network where links between nodes form a directed graph along a sequence.
This allows it to exhibit temporary dynamic behavior for a time sequence.
Apart from forward neural networks i.e. RNNs which can use their internal state to process range of inputs.
This makes them open to works such as unsegmented linked handwriting recognition/speech recognition.
Term "recurrent neural network" is used to refer to two broad classes of networks with a same structure where one is finite impulse and other infinite impulse.
Neural networks: A mathematical model used to predict and classify results from the given data set is referred to as neural networks.
They are also called as artificial neural networks.
They contain a set of algorithms and functions similar to that of a neuron of the brain.
A neural network classifies the inputs by the process of learning.
Recurrent Neural Networks: A type of artificial neural network which has to inputs.
- Present
- Immediate past.
Hence, the exhibit dynamic behavior and can recognize and identify a wide range of patterns and texts.
They can be used to identify trends and classify text more effectively.
The given statement is true.