Recurrent Neural Network Tutorial (RNN)

Learn about the most popular deep learning model RNN and get hands-on experience by building a MasterCard stock price predictor.


What are Recurrent Neural Networks (RNN)

A recurrent neural network (RNN) is the type of artificial neural network (ANN) that is used in Apple’s Siri and Google’s voice search. RNN remembers past inputs due to an internal memory which is useful for predicting stock prices, generating text, transcriptions, and machine translation.

In the traditional neural network, the inputs and the outputs are independent of each other, whereas the output in RNN is dependent on prior elementals within the sequence. Recurrent networks also share parameters across each layer of the network. In feedforward networks, there are different weights across each node. Whereas RNN shares the same weights within each layer of the network and during gradient descent, the weights and basis are adjusted individually to reduce the loss.

Read more: Recurrent Neural Network Tutorial (RNN) - DataCamp