Artificial Intelligence Neural Networks 2

Question 1

What distinguishes a convolutional neural network (CNN) from a standard feedforward network?

Accepted Answer

CNNs apply learnable filters that share weights spatially

Answer

CNNs use convolutional filters with shared weights to detect local patterns efficiently, especially in image data.

Question 2

What is the purpose of a pooling layer in a CNN?

Accepted Answer

Reduce spatial dimensions and provide translational invariance

Answer

Pooling (e.g., max pooling) downsamples feature maps, reducing computation and making features more invariant to small shifts.

Question 3

What is batch normalization designed to do?

Accepted Answer

Normalize layer inputs to speed up and stabilize training

Answer

Batch normalization normalizes activations within a mini-batch, reducing internal covariate shift and allowing higher learning rates.

Question 4

In a recurrent neural network (RNN), what makes it suitable for sequential data?

Accepted Answer

It maintains a hidden state that captures information from previous time steps

Answer

RNNs pass a hidden state from one time step to the next, allowing the network to remember previous inputs.

Question 5

What problem do LSTMs (Long Short-Term Memory networks) solve compared to standard RNNs?

Accepted Answer

Vanishing gradients over long sequences

Answer

LSTMs use gating mechanisms (forget, input, output gates) to maintain gradients over long sequences, addressing the vanishing gradient problem.

Artificial Intelligence Practice Test