#### Q61: It is better to utilize the nearest neighbor method…

- (A) with large-sized datasets
- (B) when irrelevant attributes have been removed from the data
- (C) when a generalized model of the data is desirable
- (D) when an explanation of what has been found is of primary importance

#### Q62: Assume we computed the gradient of our cost function and saved it in a vector g. Given the gradient, what is the cost of one gradient descent update?

- (A) O(D)
- (B) O(N)
- (C) O(ND)
- (D) O(ND
^{2})

#### Q63: The process of forming general concept definitions from examples of concepts to be learned

- (A) Deduction
- (B) abduction
- (C) induction
- (D) conjunction

#### Q64: While fitting a linear regression to the data, you see the following: As the amount of training data grows, the test error reduces but the training error increases. The train error is pretty low (nearly as low as you would anticipate), while the test error is significantly greater than the train error. What do you believe is the primary cause for this behavior? Select the most likely option.

- (A) High variance
- (B) High model bias
- (C) High estimation bias
- (D) None of the above

#### Q65: What would you do in PCA to get the same projection as SVD?

- (A) Transform data to zero mean
- (B) Transform data to zero median
- (C) Not possible
- (D) None of these

#### Q66: When doing least-squares regression with regularization (assuming that the optimization can be done exactly), increasing the value of the regularization parameter λ

- (A) will never decrease the training error.
- (B) will never decrease the training error.
- (C) will never decrease the testing error.
- (D) may either increase or decrease the testing error.

#### Q67: In neural networks, nonlinear activation functions such as sigmoid, tanh, and ReLU

- (A) speed up the gradient calculation in backpropagation, as compared to linear units
- (B) help to learn nonlinear decision boundaries
- (C) are applied only to the output units
- (D) always output values between 0 and 1

#### Q68: In univariate linear least squares regression, relationship between correlation coefficient and coefficient of determination is ______?

- (A) Both are unrelated False
- (B) The coefficient of determination is the coefficient of correlation squared True
- (C) The coefficient of determination is the square root of the coefficient of correlation False
- (D) Both are same

#### Q69: Tony draws four cards at random from a 52-card deck and replaces them in the deck ( Any set of 4 cards is equally likely ). Then, Alex draws 8 cards at random from the same deck ( Any set of 8 cards is equally likely). Assume that Tony’s selection of four cards and Alex’s selection of eight cards are independent. What is the likelihood that all four cards chosen by Tony are included in the set of eight cards picked by Alex?

- (A)
^{48}C_{4}x^{52}C_{4} - (B)
^{48}C_{4}x^{52}C_{8} - (C)
^{48}C_{8}x^{52}C_{8} - (D) None of the above

#### Q70: Assume you were interviewed for a technical position. Half of those who attended the initial interview were called back for a second interview. 95 percent of those who received a call for a second interview were pleased with their initial interview. Seventy-five percent of those who did not receive a second call were satisfied with their first interview. What is the likelihood that you will be called for a second interview if you feel well after your first?

- (A) 66%
- (B) 56%
- (C) 75%
- (D) 85%

## Answers:

Question | Q61 | Q62 | Q63 | Q64 | Q65 | Q66 | Q67 | Q68 | Q69 | Q70 |

Answer | B | A | C | A | A | A | B | B | A | B |