Machine Learning Machine Learning 3

Question 1

What is the vanishing gradient problem in deep neural networks?

Accepted Answer

Gradients shrink to near zero as they propagate back through layers, halting learning

Answer

The vanishing gradient problem occurs when gradients become exponentially small during backpropagation through many layers, preventing earlier layers from learning effectively.

Question 2

Which cross-validation strategy is most appropriate for time-series data?

Accepted Answer

Walk-forward (time series) cross-validation

Answer

Walk-forward cross-validation respects temporal order by only using past data to predict future data, preventing data leakage from future observations.

Question 3

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

Accepted Answer

To introduce non-linearity so the network can learn complex patterns

Answer

Activation functions introduce non-linearity into the network, allowing it to learn and represent complex, non-linear relationships in data.

Question 4

Which metric is most suitable for evaluating a model on a highly imbalanced classification dataset?

Accepted Answer

F1-Score

Answer

F1-Score, the harmonic mean of precision and recall, is preferred for imbalanced datasets because accuracy can be misleadingly high when the majority class dominates.

Question 5

What is transfer learning in machine learning?

Accepted Answer

Using a pre-trained model's learned representations as a starting point for a new task

Answer

Transfer learning leverages knowledge (weights and representations) from a model trained on one task to improve learning on a related but different task.

Machine Learning Practice Test

Machine Learning Practice Test

Machine Learning Machine Learning 3