Free iSQI CT-AI_v1.0_World Exam Questions

Question 1

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.

A : F1 –source

B : Precision

C : Recall

D : Accuracy

Answer: D

Question 2

Which machine learning approach is most suitable for predicting customer purchase probability? Choose ONE option (1 out of 4)

A : Supervised learning (regression)

B : Supervised learning (classification)

C : Unsupervised learning

D : Reinforcement learning

Answer: B

Question 3

A startup company has implemented a new facial recognition system for a banking application for mobile devices. The application is intended to learn at run-time on the device to determine if the user should be granted access. It also sends feedback over the Internet to the application developers. The application deployment resulted in continuous restarts of the mobile devices. Which of the following is the most likely cause of the failure?

A : The feedback requires a physical connection and cannot be sent over the Internet.

B : Mobile operating systems cannot process machine learning algorithms.

C : The size of the application is consuming too much of the phone-s storage capacity.

D : The training, processing, and diagnostic generation are too computationally intensive for the mobile device hardware to handle.

Answer: D

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.

A : F1 –source

B : Precision

C : Recall

D : Accuracy

Answer: D

Question 5

Which of the following is correct regarding the layers of a deep neural network?

A : There is only an input and output layer

B : There is at least one internal hidden layer

C : There must be a minimum of five total layers to be considered deep

D : The output layer is not connected with the other layers to maintain integrity

Answer: B