1. 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.
2. Which of the following is a real-world application of AI in finance?
A. Fraud detection
B. Voice assistants
C. Image classification
D. Self-driving cars
Answer: a) Fraud detection
,Rationale: AI is widely used in finance for detecting fraud by analyzing patterns and
anomalies in transactions.
3. In which phase does a machine learning model evaluate its performance using data
that it hasn’t seen before?
A. Training
B. Testing
C. Validation
D. Deployment
Answer: b) Testing
Rationale: Testing evaluates a model's performance on unseen data to ensure it
generalizes well.
4. Which AI technique is used in AlphaGo, the AI that defeated a human champion in
Go?
A. Deep Q-Learning
B. Decision Trees
C. Support Vector Machines
D. K-means Clustering
, Answer: a) Deep Q-Learning
Rationale: AlphaGo used deep reinforcement learning, combining deep neural
networks and Q-learning, to train and optimize its gameplay strategy.
5. What is a "decision boundary" in classification problems?
A. The threshold for determining when to stop training
B. The point where the model's prediction changes
C. A rule for dividing the training data into separate groups
D. The line that separates training and testing data
Answer: b) The point where the model's prediction changes
Rationale: The decision boundary is the dividing line or surface that separates
different classes based on the features of the data.
6. 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
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.
2. Which of the following is a real-world application of AI in finance?
A. Fraud detection
B. Voice assistants
C. Image classification
D. Self-driving cars
Answer: a) Fraud detection
,Rationale: AI is widely used in finance for detecting fraud by analyzing patterns and
anomalies in transactions.
3. In which phase does a machine learning model evaluate its performance using data
that it hasn’t seen before?
A. Training
B. Testing
C. Validation
D. Deployment
Answer: b) Testing
Rationale: Testing evaluates a model's performance on unseen data to ensure it
generalizes well.
4. Which AI technique is used in AlphaGo, the AI that defeated a human champion in
Go?
A. Deep Q-Learning
B. Decision Trees
C. Support Vector Machines
D. K-means Clustering
, Answer: a) Deep Q-Learning
Rationale: AlphaGo used deep reinforcement learning, combining deep neural
networks and Q-learning, to train and optimize its gameplay strategy.
5. What is a "decision boundary" in classification problems?
A. The threshold for determining when to stop training
B. The point where the model's prediction changes
C. A rule for dividing the training data into separate groups
D. The line that separates training and testing data
Answer: b) The point where the model's prediction changes
Rationale: The decision boundary is the dividing line or surface that separates
different classes based on the features of the data.
6. 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
