Which of the following best describes the primary purpose of Long Short-Term Memory (LSTM) networks in deep learning? 单项选择题

A

To convert non-sequential data into sequential data

B

To solve the vanishing gradient problem and effectively learn long-term dependencies in sequential data

C

To increase the speed of training by using parallel processing

D

To reduce the number of parameters in a neural network

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What problem does LSTM solve that basic RNNs struggle with? 

  What are the drawbacks of Recurrent Neural Networks (RNNs)?   I RNNs can only solve regression problems. II RNNs can only produce single-valued outputs. III RNNs suffer from vanishing gradients, which make it difficult to know which direction the parameters should move, and exploding gradients, which can make learning unstable. IV One can only use the sigmoid function as the activation function for its hidden layers.  

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