Java: Data Science Made Easy

Recurrent Neural Networks

RNN differ from feed-forward networks in that their input includes the input from the previous iteration or step. They still process the current input but use a feedback loop to take into consideration the inputs to the prior step, also called the recent past, for context. This step effectively gives the network memory. One popular type of recurrent network involves Long Short-Term Memory (LSTM). This type of memory improves the processing power of the network.

RNNs are designed to process sequential data and are especially useful for analysis and prediction with text data. Given a sequence of words, an RNN can predict the probability of each word being the next in the sequence. This also allows for text generation ...