APPLICATION OF SUPERVISED LEARNING
NEURAL NETWORK
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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they perform the same task for every element of a sequence, with the output being depended on the previous computations.
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RNN or Recurrent Neural Network
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CNN or Convolution Neural Network
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LSTMor Long-Short Term Memory
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None of the above
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Explanation:
Detailed explanation-1: -RNNs are called recurrent because they perform the same task for every element of a sequence, with the output being depended on the previous computations.
Detailed explanation-2: -RNNs are designed to handle input sequences of variable length, which makes them well-suited for tasks such as speech recognition, natural language processing, and time series analysis.
Detailed explanation-3: -Difference between RNN and Feed-forward neural network Recurrent neural networks contain a feedback loop that allows data to be recycled back into the input before being forwarded again for further processing and final output. Whereas feedforward neural networks just forward data from input to output.
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