Question 1

When selecting an appropriate ML approach, which of the following guidelines does NOT apply?

Options :

A : Reinforcement learning is better suited to contexts in which there is interaction with the environment.

B : For unsupervised learning, it is necessary to have properly labeled data.

C :

There should be sufficient training and test data available for the selected ML approach.

D : If the problem involves the notion of multiple states, and involves decisions at each state, then reinforcement learning may be applicable.

Answer: B

Question 2

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 3

“A dataset used to evaluate a trained ML model with the purpose of tuning the model”

Options :

A : Validation dataset

B :

Evaluation dataset

C : Training dataset

D : Tuning dataset

Answer: A

Question 4

Consider a machine learning model where the model is attempting to predict if a patient is at risk for stroke. The model collects information on each patient regarding their blood pressure, red blood cell count, smoking, status, history of heart disease, cholesterol level, and demographics. Then, using a decision tree the model predicts whether or not the associated patient is likely to have a stroke in the near future. One the model is created using a training data set, it is used to predict a stroke in 80 additional patients. The table below shows a confusion matrix on whether or not the model mode a correct or incorrect prediction. The testers have calculated what they believe to be an appropriate functional performance metric for the model. They calculated a value of 2/3 or 0.6667.

Options :

A :

F1 –source

B : Precision

C : Recall

D : Accuracy

Answer: D

Question 5

What is the correct definition for the term "fuzzy logic"?

Options :

A : The ability of a system to work in contexts outside its initial specification

B : A type of logic based on the concept of partial truth represented by certainty factors between 0 and 1

C : An individual measurable attribute of the input data used for training by an ML algorithm and for prediction by an ML model

D : An ML functional performance metric used to evaluate a classifier which provides a balance between recall and precision

Answer: B