1. In a neural network, what does "backpropagation" do?
A. It adjusts the weights based on the error gradient
B. It generates the training data for the model
C. It splits the data into training and testing sets
D. It determines the number of layers in the network
Answer: a) It adjusts the weights based on the error gradient
Rationale: Backpropagation is used to compute gradients of the error with respect to
the weights and update the weights accordingly to minimize the error.
2. What is the role of the "learning rate" in training a machine learning model?
A. It determines how quickly the model's performance improves
B. It controls the complexity of the model
C. It determines the number of epochs to train for
D. It decides which features to use in the model
Answer: a) It determines how quickly the model's performance improves
Rationale: The learning rate controls the step size used to update the model’s weights
during training, affecting how fast or slow the model learns.
,3. In AI, what does "transfer learning" refer to?
A. Using a pre-trained model on a new task with little additional training
B. Sharing learned data between two models
C. The ability of AI to improve through experience
D. None of the above
Answer: a) Using a pre-trained model on a new task with little additional training
Rationale: Transfer learning involves taking a model trained on one task and adapting
it to a different but related task, reducing the amount of training needed.
4. What does "reinforcement learning" focus on?
A. Training models with labeled data
B. Learning from the environment through rewards and penalties
C. Identifying patterns in unlabeled data
D. Reducing the complexity of models
Answer: b) Learning from the environment through rewards and penalties
Rationale: Reinforcement learning involves agents learning to make decisions by
interacting with an environment and receiving rewards or penalties based on their
actions.
, 5. Which of the following is a type of machine learning algorithm that can be used for
clustering?
A. K-means
B. Logistic regression
C. Linear regression
D. Decision tree
Answer: a) K-means
Rationale: K-means is an unsupervised learning algorithm used for clustering data
into groups based on similarity.
6. Which AI technique is used to simulate the behavior of the human brain in
processing information?
A. Neural networks
B. Genetic algorithms
C. Fuzzy logic
D. Expert systems
Answer: a) Neural networks
A. It adjusts the weights based on the error gradient
B. It generates the training data for the model
C. It splits the data into training and testing sets
D. It determines the number of layers in the network
Answer: a) It adjusts the weights based on the error gradient
Rationale: Backpropagation is used to compute gradients of the error with respect to
the weights and update the weights accordingly to minimize the error.
2. What is the role of the "learning rate" in training a machine learning model?
A. It determines how quickly the model's performance improves
B. It controls the complexity of the model
C. It determines the number of epochs to train for
D. It decides which features to use in the model
Answer: a) It determines how quickly the model's performance improves
Rationale: The learning rate controls the step size used to update the model’s weights
during training, affecting how fast or slow the model learns.
,3. In AI, what does "transfer learning" refer to?
A. Using a pre-trained model on a new task with little additional training
B. Sharing learned data between two models
C. The ability of AI to improve through experience
D. None of the above
Answer: a) Using a pre-trained model on a new task with little additional training
Rationale: Transfer learning involves taking a model trained on one task and adapting
it to a different but related task, reducing the amount of training needed.
4. What does "reinforcement learning" focus on?
A. Training models with labeled data
B. Learning from the environment through rewards and penalties
C. Identifying patterns in unlabeled data
D. Reducing the complexity of models
Answer: b) Learning from the environment through rewards and penalties
Rationale: Reinforcement learning involves agents learning to make decisions by
interacting with an environment and receiving rewards or penalties based on their
actions.
, 5. Which of the following is a type of machine learning algorithm that can be used for
clustering?
A. K-means
B. Logistic regression
C. Linear regression
D. Decision tree
Answer: a) K-means
Rationale: K-means is an unsupervised learning algorithm used for clustering data
into groups based on similarity.
6. Which AI technique is used to simulate the behavior of the human brain in
processing information?
A. Neural networks
B. Genetic algorithms
C. Fuzzy logic
D. Expert systems
Answer: a) Neural networks
