Capture patterns with recurrent neural networks

1.

We want to train a neural network to generate new funny words for children's book. Which architecture can we use?

Word-level LSTM

Character-level LSTM

Word-level RNN

Character-level perceptron

2.

Recurrent neural network is called recurrent, because:

A network is applied for each input element, and output from the previous application is passed to the next one

It's trained by a recurrent process

It consists of layers that include other subnetworks

3.

What is the main idea behind LSTM network architecture?

Fixed number of LSTM blocks for the whole dataset

It contains many layers of recurrent neural networks

Explicit state management with forgetting and state triggering

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