Question 1

What is the primary objective of feature importance analysis in machine learning?

Options :

A : To select the best hyperparameters for the model

B : To preprocess the input data before training the model

C : To identify the most influential features for predicting the target variable

D : To evaluate the performance of a trained model

Answer: C

Question 2

In machine learning, what technique is commonly used for handling class imbalance?

Options :

A : Oversampling the minority class

B : All of the above

C : Undersampling the majority class

D : SMOTE

Answer: B

Question 3

Which of the following is a tree-based ensemble learning algorithm that builds multiple decision trees and merges them together to get a more accurate and stable prediction?

Options :

A : Decision tree

B : Random forest

C : Bagging

D : Gradient boosting

Answer: B

Question 4

What principle emphasizes the importance of integrating data science workflows with development and operations processes to streamline deployment and maintenance?

Options :

A : MLOps

B : Data replication

C : DevOps

D : Continuous integration/continuous deployment

Answer: A

Question 5

What process involves transforming data into a standard format suitable for analysis or modeling?

Options :

A : Data visualization

B : Feature engineering

C : Data preprocessing

D : Model evaluation

Answer: C

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