Neural Network Deep Learning Architectures

Question 1

What distinguishes a deep neural network from a shallow neural network?

Accepted Answer

It has multiple hidden layers

Answer

It uses GPU acceleration

Answer

It requires more training data

Answer

It uses a different loss function

Question 2

Which architecture is specifically designed for processing sequential data with long-range dependencies?

Accepted Answer

Transformer

Answer

Convolutional Neural Network

Answer

Autoencoder

Answer

Restricted Boltzmann Machine

Question 3

What is the primary role of the encoder in an autoencoder network?

Accepted Answer

To compress input into a latent representation

Answer

To classify input data

Answer

To generate new samples

Answer

To apply dropout regularization

Question 4

In a Generative Adversarial Network (GAN), what is the role of the discriminator?

Accepted Answer

To distinguish real samples from generated ones

Answer

To generate realistic samples

Answer

To encode latent variables

Answer

To apply weight regularization

Question 5

Which component of a Variational Autoencoder (VAE) enables backpropagation through the sampling step?

Accepted Answer

The reparameterization trick

Answer

The KL divergence term

Answer

The reconstruction loss

Answer

The encoder bottleneck

Question 6

What is residual learning in the context of deep neural networks?

Accepted Answer

Adding skip connections so layers learn residual mappings

Answer

Learning from leftover training data

Answer

Using dropout to reduce overfitting

Answer

Training with smaller learning rates