Recurrent Neural Networks (RNNs)

Recurrent Neural Networks, or RNNs, are a type of neural network specially designed for sequential data, like words in text or time series in finance data.

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Unlike traditional networks, RNNs have a memory element. They process sequences step by step, retaining information from previous steps. This 'memory' allows them to make predictions considering the context of earlier data. RNNs are used for tasks like language translation, where understanding the sequence of words is crucial. However, RNNs face challenges like the vanishing gradient problem, making them less efficient for long sequences. That's where advanced versions like LSTMs and GRUs come in.