Question 1

Why is it important to standardize data formats in data preparation?

Options :

A : To reduce data volume

B : To ensure consistency across datasets

C : To increase data privacy

D : To simplify data cleaning

Answer: B

Question 2

What is the role of a model’s "learning rate" in training?

Options :

A : It controls the speed at which the model learns from data

B : It determines the number of features used

C : It adjusts the model-s complexity

D : It modifies the data distribution

Answer: A

Question 3

What type of model helps in making decisions about future actions based on data?

Options :

A : Descriptive model

B : Predictive model

C : Prescriptive model

D : Diagnostic model

Answer: C

Question 4

What is an alternative hypothesis?

Options :

A : A hypothesis that is not testable

B : A hypothesis that contradicts the null hypothesis

C : A hypothesis that is always true

D : A hypothesis used for data cleaning

Answer: B

Question 5

What is "grid search" in the context of model tuning?

Options :

A : A technique to optimize hyperparameters by exhaustively searching through a predefined set

B : A method to evaluate multiple models simultaneously

C : A way to preprocess data for modeling

D : A technique for selecting features

Answer: A

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