RNN

What Does RNN Mean?

The Quick Answer

RNN means "Recurrent Neural Networks."

More Observations...

Recurrent Neural Networks (RNNs) are a type of artificial intelligence (AI) that can remember previous information in a sequence. This makes them useful for tasks like speech recognition and language modeling.

In Detail

RNNs are a class of artificial neural networks (ANN) designed for processing sequences of data. Unlike traditional "feedforward" networks, RNNs have connections looping back within the network, allowing information to persist. This architecture enables them to remember previous inputs in the sequence, making them suitable for tasks like speech recognition, language modeling, and time-series prediction. RNNs can be challenging to train, especially with long sequences, leading to problems like vanishing or exploding gradients. Variations like Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) networks have been developed to address these issues, making RNNs more effective and versatile.

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When I write RNN, I mean this:

"Recurrent Neural Networks"

Summary of Key Points

"Recurrent Neural Networks" is, by far, the most common meaning for RNN when it is used in a text. (Bear in mind that it could have another meaning if used in a different context.)