How does the implementation of a Convolutional Neural Network (CNN) differ from a Recurrent Neural Network (RNN) when processing images and sequential data, respectively?

CNNs are designed for spatial data like images, using convolutional layers to detect patterns. RNNs, on the other hand, are tailored for sequential data, utilizing recurrent connections to maintain temporal dependencies. CNNs excel in image recognition tasks, while RNNs are ideal for tasks like language modeling and time series prediction.

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