1. Which of the following is a supervised learning problem?

• Grouping people in a social network.
• Predicting credit approval based on historical data
• Predicting rainfall based on historical data
• all of the above

Answer : b, c

2. Which of the following are classification problems? (multiple options may be correct)

• Predicting the temperature (in Celsius) of a room from other environmental features (such as atmospheric pressure, humidity etc).
• Predicting if a cricket player is a batsman or bowler given his playing records.
• Predicting if a particular route between two points has traffic jam or not based on the travel time of vehicles.
• Filtering of spam messages

Answer : b, c, d

3. Which of the following is a regression task? (multiple options may be correct)

• Predicting the monthly sales of a cloth store in rupees.
• Predicting if a user would like to listen to a newly released song or not based on historical data.
• Predicting the confirmation probability (in fraction) of your train ticket whose current status is waiting list based on historical data.
• Predicting if a patient has diabetes or not based on historical medical records.
• Predicting the gender of a human based on facial features.

Answer : a, c

4. Which of the following is an unsupervised task?

• Learning to play chess.
• Predicting if a new edible item is sweet or spicy based on the information of the ingredients, their quantities, and labels (sweet or spicy) for many other similar dishes.
• Grouping related documents from an unannotated corpus.
• all of the above

Answer : c

5. Which of the following is a categorical feature?

• Number of legs of an animal
• Number of hours you study in a day
• Your weekly expenditure in rupees.
• Branch of an engineering student
• Ethnicity of a person
• Height of a person in inches

Answer : d, e

6. Let X and Y be a uniformly distributed random variable over the interval [0, 4] and [0, 6] respectively. If X and Y are independent events, then compute the probability, P (max(X, Y ) > 2)

Answer : b

7.

Answer : b

8. What happens when your model complexity increases? (multiple options may be correct)

• Model Bias decreases
• Model Bias increases
• Variance of the model decreases
• Variance of the model increases

Answer : a, d

9. Based on a survey, it was found that the probability that a student likes to play football was 0.25 and the probability that a student likes to play cricket is 0.43. It was also found that the probability that a student likes to play both football and cricket is 0.12. What is the probability that a student does not like to play either?

• 0.32
• 0.2
• 0.44
• 0.56

Answer : c

10. Which of the following are true about bias and variance of overfitted and underfitted models? (multiple options may be correct)

• Underfitted models have high bias.
• Underfitted models have low bias.
• Overfitted models have low variance.
• Overfitted models have high variance.
• none of these

Answer : a, d