How Digital Assistants Work

What type of problem is it if the prediction variable is a number?

• A. Classification

• B. Regression

• C. Reinforcement

• D. Unsupervised

Does the type of features in the dataset affect whether a problem is a classification or regression?

• A. Yes, features must be numerical for regression

• B. Yes, features must be categorical for classification

• C. No, the type of features does not matter

• D. Yes, features must match the type of problem

What is the label in the given table example?

• A. The first four columns

• B. A category

• C. The average of the first four columns

• D. The type of problem

Why should we not use AI for simple tasks like calculating averages?

• A. Because AI cannot handle simple tasks

• B. Because AI is meant for complex pattern recognition

• C. Because calculators are cheaper

• D. Because AI needs more data for simple tasks

What kind of data is appropriate for using AI in the mood dataset?

• A. Numerical data

• B. Categorical data

• C. Text data

• D. Image data

How is the error of a regression AI calculated?

• A. By counting correct predictions

• B. By finding the difference between predicted and actual values

• C. By multiplying predicted values

• D. By dividing the total predictions

What is the absolute value of an error?

• A. The negative of the error

• B. The error divided by the number of predictions

• C. The error without considering its sign (positive or negative)

• D. The error squared

What is mean absolute error (MAE)?

• A. The average of squared errors

• B. The total error divided by the number of predictions

• C. The average of absolute errors

• D. The square root of the total error

Why might root mean square error (RMSE) be used instead of mean absolute error (MAE)?

• A. RMSE penalizes larger errors more heavily

• B. RMSE is easier to calculate

• C. RMSE is a smaller value than MAE

• D. RMSE ignores smaller errors

What is GPS used for in digital assistants like Google Maps?

• A. To calculate averages

• B. To recognize speech

• C. To track your location

• D. To predict weather