Question 1

When performing testing of a trained model, an ML engineer found that the model was highly accurate when evaluated with validation data but that it performed poorly with independent test data.

Which of the following options is MOST likely to cause this situation?

Options :

A : Poor acceptance criteria

B : Underfitting

C : Overfitting

D : Concept drift

Answer: C

Question 2

In the figure below there are three scatter plots and a freehand sketch for logistics regression.

Which of the above figures show that the decision boundary is overfitting the training data?

Options :

A : None of the above

B : A

C : B

D : C

Answer: D

Question 3

Which of the following AI hardware best matches with the processor?

Options :

A : Huawei-Intense vision processing

B : Mobileye- Al (B05)

C :

Intel- Bionic chip

D : NVIDIA- Al-specific processors for example (R09) Volta.

Answer: D

Question 4

Insufficient specifications of operational environment is a critical challenge when testing self-learning systems. The tendency to have environmental inputs outside the set scope poses a danger to the testing process.

Which of the following statements isMOSTlikely be specifying a solution to Insufficient specifications of operational environment?

Options :

A : Install constraints for behavioral modifications and responses to the external factors in the operational environment

B : Limiting the impact from external environmental factors

C : Using a wider and full scope of possible changes in the operational environment to which the system is expected to respond

D : Focusing on the results from the inputs with the speculated range

Answer: C

Question 5

Biases introduce the chance of getting unwanted output from ML systems. Testing for biases allows the identification of errors and causal defects that can further help review datasets and remove unwanted biases.

Which ONE among the following options is not a bias in AI based systems?

Options :

A : Algorithmic bias

B : Sample bias

C : Autonomous bias

D : Inappropriate bias

Answer: C