AI Fundamentals Quiz

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Question 1: Which component of a convolutional neural network extracts spatial features from images?

A. Fully connected layer

B. Softmax layer

C. Convolutional layer

D. Dropout layer

Question 2: What is the primary benefit of using transfer learning for computer vision tasks?

A. It guarantees 100% accuracy on new tasks

B. It lets a model reuse learned features from a related task

C. It removes the need for labeled data entirely

D. It makes training models slower but more stable

Question 3: Which metric is most appropriate to evaluate a binary classifier on imbalanced data?

A. Accuracy

B. Mean squared error

C. Precision-recall AUC

D. Log loss alone

Question 4: What does the temperature parameter control in large language model sampling?

A. The number of training epochs

B. The softmax sharpness when generating tokens

C. The context window size

D. The token embedding dimension

Question 5: Which approach helps a reinforcement learning agent balance exploration and exploitation?

A. Using an epsilon-greedy policy

B. Freezing the replay buffer

C. Removing reward shaping

D. Disabling policy gradients