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Question 1

Which of the following evaluation metrics is not suitable to evaluate runs in AutoML experiments for regression problems?

Options :

A : F1

B : R-squared

C : MAE

D : MSE

Answer: A

Question 2

What is the name of the method that transforms categorical features into a series of binary indicator feature variables?

Options :

A : Leave-one-out encoding

B : Target encoding

C : One-hot encoding

D : Categorical embeddings

E : String indexing

Answer: C

Question 3

What is the name of the method that transforms categorical features into a series of binary indicator feature variables?

Options :

A : Leave-one-out encoding

B : Target encoding

C : One-hot encoding

D : Categorical embeddings

E : String indexing

Answer: C

Question 4

A machine learning engineer is using the following code block to scale the inference of a single-node model on a Spark DataFrame with one million records:

Assuming the default Spark configuration is in place, which of the following is a benefit of using an Iterator?

Options :

A : The data will be limited to a single executor preventing the model from being loaded multiple times

B : The model will be limited to a single executor preventing the data from being distributed

C : The model only needs to be loaded once per executor rather than once per batch during the inference process

D : The data will be distributed across multiple executors during the inference process

Answer: C

Question 5

Which of the following evaluation metrics is not suitable to evaluate runs in AutoML experiments for regression problems?

Options :

A : F1

B : R-squared

C : MAE

D : MSE

Answer: A