Artificial Intelligence Neural Networks

Question 1

What is the role of an activation function in a neural network?

Accepted Answer

Introduce non-linearity into the model

Answer

Activation functions add non-linearity, allowing neural networks to learn complex patterns beyond linear mappings.

Question 2

Which activation function outputs values between 0 and 1 and is commonly used in binary classification output layers?

Accepted Answer

Sigmoid

Answer

The sigmoid function maps any real number to (0,1), making it suitable for binary probability outputs.

Question 3

What is backpropagation in neural network training?

Accepted Answer

Using the chain rule to compute gradients and update weights

Answer

Backpropagation computes gradients of the loss with respect to all weights by applying the chain rule backwards through the network.

Question 4

What is a 'vanishing gradient' problem in deep neural networks?

Accepted Answer

Gradients shrink to near zero as they propagate back, slowing learning in early layers

Answer

Vanishing gradients occur when gradients become too small during backpropagation, preventing early layers from learning effectively.

Question 5

Which layer type in a neural network is fully connected, meaning every input neuron links to every output neuron?

Accepted Answer

Dense (fully connected) layer

Answer

A dense layer connects every neuron in the previous layer to every neuron in the next layer.

Artificial Intelligence Practice Test