# Machine learning mcq question with answer for exam and interview preperation.

1. Choose the options that is incorrect regarding machine learning (ML) and

artificial intelligence (AI)

A. ML is an alternate way of programming intelligent machines

b. ML and AI have very different goals

C. ML is a set of techniques that turns a dataset into a software

D. AI is a software that can emulate the human mind

Answer is B) - ML and AI have very different goals.

2. Which of the following sentence is FALSE regarding regression

A. It is used for prediction

B. It may be used for interpretation

C. It relates inputs to outputs.

D. It discovers causal relationships

Answer is D) - It discovers casual relationships

3. Grid search is

A. Linear in D

B. Exponential in D

C. Linear in N

D. Both B & C

Answer is D) - Bot B & C

4. Find incorrect regarding Gradient of a continuous and differentiable function

A. is zero at a minimum

B. is non-zero at a maximum

C. is zero at a saddle point

D. decreases as you get closer to the minimum

Answer is B) - Is non zero at maximum

5. Consider a linear-regression model with N = 3 and D = 1 with input-ouput pairs as follows: y1 = 22, x1 = 1, y2 = 3, x2 = 1, y3 = 3, x3 = 2. What is the gradient of mean-square error (MSE) with respect to β1 when β0 = 0 and β1 = 1? Give your answer correct to two decimal digits.

A. -1.66

B. 2

C. 3

D. 4

Answer is A) -1.66

6. Let us say that we have computed the gradient of our cost function and stored it in a vector g. What is the cost of one gradient descent update given the gradient?

A. O(D)

B. O(N)

C. O(ND)

D. O(ND2)

Answer is A) - O(D)

7. You observe the following while fitting a linear regression to the data: As you increase the amount of training data, the test error decreases and the training error increases. The train error is quite low (almost what you expect it to), while the test error is much higher than the train error. What do you think is the main reason behind this behavior. Choose the most probable option

A. High variance

B. High model bias

C. High estimation bias

D. All of the above

Answer is A) - High Variance

8. Adding more basis functions in a linear model...

A. Decreases model bias

B. Decreases estimation bias

C. Decreases variance

D. Doesn’t affect bias and variance

Answer is A) - Decreases model bias

9. The problem of finding hidden structure in unlabeled data is called

A. Supervised learning

b. UnSupervised learning

C. Reinforcement learning

D. None of the above

Answer is B) - Unsupervised learning

10. Task of inferring a model from labeled training data is called

A. Supervised learning

b. UnSupervised learning

C. Reinforcement learning

D. None of the above

Answer is A) - Supervised learning

11. Some telecommunication company wants to segment their customers into distinct groups in order to send appropriate subscription offers, this is an example of

A. Supervised learning

B. Data Extraction

C. Serration

D. UnSupervised learning

Answer is D) - Unsupervised learning

12. Self-organizing maps are an example of

A. Unsupervised learning

B. Supervised learning

C. Reinforcement learning

D. Missing data imputation

Answer is A) - Unsupervised Learning

13. You are given data about seismic activity in Japan, and you want to predict a magnitude of the next earthquake, this is in an example of

A. Supervised learning

B. Unsupervised Learning

C. Serration

D. None of the above

Answer is A) - Supervised learning

14. Discriminating between spam and ham e-mails is a classification task, true or false?

A. True

B. False

Answer is A) True

15. In the example of predicting number of babies based on storks’ population size, number of babies is

A. Outcome

B. Feature

C. Attribute

D. None of the above

Answer is A) Outcome

16. It may be better to avoid the metric of ROC curve as it can suffer from accuracy paradox.

A. True

B. False

Answer is B) False

17. which of the following is not involve in data mining

A. Knowledge extraction

B. Data archaeology

C. Data exploration

D. Data transformation

Answer is D) Data transformation

18. The expected value or _______ of a random variable is the center of its distribution.

A. Mode

B. Median

C. Mean

D. All of the aboce

Answer is C) Mean

19. Point out the correct statement.

A. Some cumulative distribution function F is non-decreasing and right-continuous

B. Every cumulative distribution function F is decreasing and right-continuous

C. Every cumulative distribution function F is increasing and left-continuous

D. None of the above

Answer is D) None of the above

20. Which of the following of a random variable is a measure of spread

A. Variance

B. standard deviation

C. Empirical mean

D. All of the above

Answer is A) Variance