Question 1

What characteristic of a problem makes ML an ideal solution?

Options :

A : The problem can be solved with traditional methods.

B : The problem involves complex and dynamic data.

C : The problem does not require scalability.

D : The problem requires simple logic.

Answer: B

Question 2

What is a key advantage of a complex machine learning model?

Options :

A : Speed of data processing

B : High accuracy

C : Low computational requirements

D : High explainability

Answer: B

Question 3

What is the primary purpose of clustering in machine learning?

Options :

A : Grouping similar items together

B : Identifying outliers

C : Predicting future trends

D : Ranking relevant items

Answer: A

Question 4

Why is explainability important in some contexts?

Options :

A : It improves the model-s accuracy

B : It enhances the model-s speed

C : It reduces the amount of training data needed

D : It ensures that decisions can be justified and understood

Answer: D

Question 5

How is deep learning different from general machine learning?

Options :

A : It requires no domain knowledge.

B : It uses a layered architecture mimicking the human brain.

C : It relies solely on historical data.

D : It is unrelated to pattern recognition.

Answer: B