Скачать или смотреть What is the difference between a recurrent neural network and a feedforward neural network?

Answer
Recurrent neural networks (RNNs) and feedforward neural networks (FFNNs) are both types of artificial neural networks, but they have distinct characteristics and are used for different types of tasks. RNNs are designed to process sequential data, such as text, speech, and time series data. These networks have a "memory" component, which allows them to retain information from previous inputs and use it to inform the current output. On the other hand, FFNNs are typically used for non-sequential data, such as image and audio classification tasks. They do not have the same "memory" component as RNNs and process inputs independently. If you want to prepare yourself for graduate-level computer science tests on neural networks, subscribe to this channel and stay updated on this topic.
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