DSE DSE - Data Science Deep Learning and Neural Networks 1

Question 1

Which activation function is most commonly used in hidden layers of modern deep neural networks to mitigate the vanishing gradient problem?

Accepted Answer

ReLU

Answer

ReLU (Rectified Linear Unit) outputs zero for negative inputs and the input value for positive inputs, providing sparse activations that help avoid vanishing gradients during training.

Question 2

What regularization technique prevents overfitting in neural networks by randomly setting a fraction of neuron activations to zero during each training step?

Accepted Answer

Dropout

Answer

Dropout randomly deactivates a proportion of neurons during each forward pass, forcing the network to learn redundant representations and reducing co-adaptation.

Question 3

Which optimization algorithm combines momentum with adaptive per-parameter learning rates and is widely used as a default optimizer for deep learning?

Accepted Answer

Adam

Answer

Adam (Adaptive Moment Estimation) maintains both first-moment (momentum) and second-moment (per-parameter adaptive) estimates, making it robust and fast-converging for most deep learning tasks.

Question 4

What causes the 'vanishing gradient' problem in deep neural networks?

Accepted Answer

Gradients shrinking exponentially as they propagate backward through many layers with saturating activations

Answer

When gradients are repeatedly multiplied by small values (from saturating activations like sigmoid) during backpropagation, they shrink exponentially, making early-layer weights nearly impossible to update.

Question 5

Which neural network architecture was specifically designed and is primarily used for image recognition and classification tasks?

Accepted Answer

Convolutional Neural Network (CNN)

Answer

CNNs use convolutional layers with shared weight filters to detect spatial hierarchies of features in images, making them the dominant architecture for computer vision tasks.

DSE - Data Science Practice Test

DSE - Data Science Practice Test

DSE DSE - Data Science Deep Learning and Neural Networks 1