The video tutorial discusses recurrent neural networks (RNNs), focusing on creating a deep RNN example. It highlights the concept of weight sharing across time and space, and guides on designing a simple RNN architecture. The tutorial emphasizes understanding deep RNNs and the importance of weight sharing across different layers.

What is a simple example of a recurrent neural network that is termed as deep?

Can you explain which weights are shared across time in a recurrent neural network?

Describe the sharing of weights across space in a recurrent neural network.

What are the characteristics of a deep recurrent neural network architecture?

How do the weights in different layers of a recurrent neural network interact?