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In the field of deep learning, recurrent neural networks (RNNs) have emerged as a key component, especially for processing sequential input such as text, audio, and time series. RNNs possess loops that enable them to retain information over time steps, which sets them apart from standard feed forward neural networks and makes them particularly effective for jobs requiring context. This article will explore the role that RNNs play in deep learning, including how to train them efficiently and which courses are the best to become proficient in them.
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