AI For Beginners 3

Question 1

What is a 'hyperparameter' in the context of machine learning?

Accepted Answer

A configuration set before training that controls the learning process

Answer

Hyperparameters like learning rate and layer count are set by the engineer before training, not learned from data.

Question 2

Which technique randomly drops neurons during training to reduce overfitting?

Accepted Answer

Dropout

Answer

Dropout randomly deactivates a fraction of neurons during each training step, forcing the network to learn redundant representations.

Question 3

What does 'transfer learning' allow an AI engineer to do?

Accepted Answer

Reuse a pre-trained model's knowledge for a new but related task

Answer

Transfer learning leverages representations learned on a large dataset (e.g., ImageNet) to accelerate training on a smaller target task.

Question 4

In a confusion matrix for binary classification, what does a 'false positive' represent?

Accepted Answer

The model predicted positive but the true label is negative

Answer

A false positive (Type I error) occurs when the model incorrectly labels a negative example as positive.

Question 5

What is the role of the learning rate in gradient descent?

Accepted Answer

It controls how large a step is taken in the direction of the gradient

Answer

The learning rate scales the gradient update; too high causes divergence, too low causes very slow convergence.

AI - Engineer Practice Test