Question 1

DataSure is a start-up with a product that promises to improve the quality of ML models. DataSure claim that this improvement comes from checking if the data has been labeled correctly.

Which of the following defects is MOST likely to have been prevented by using this product?

Options :

A : The model will have poor accuracy

B : The model will not fulfill its intended function

C : The model will have security vulnerabilities

D : The model will produce biased outputs

Answer: A

Question 2

Which of the following is an example of an input change where it would be expected that the AI system should be able to adapt?

Options :

A : It has been trained to recognize cats and is given an image of a dog.

B : It has been trained to recognize human faces at a particular resolution and it is given a human face image captured with a higher resolution.

C : It has been trained to analyze mathematical models and is given a set of landscape pictures to classify.

D : It has been trained to analyze customer buying trend data and is given information on supplier cost data.

Answer: B

Question 3

“An ML technique in which the data points are viewed as vectors in multi-dimensional space separated by a hyperplane”

Options :

A : Search algorithm

B : Support vector machine (SVM)

C : Sample bias

D : silhouette coefficient

Answer: B

Question 4

An integrated circuit designed to mimic the biological neurons of the human brain

Options :

A : Neural network trojan

B : Neural network

C : Neuromorphic processor

D : Natural language processing (NLP)

Answer: C

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

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