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SASInstitute SAS® Viya® Supervised Machine Learning Pipelines Sample Questions:

1. When deploying a machine learning model, what is "model drift"?

A) A sudden increase in the model's accuracy
B) A measure of feature importance
C) The process of feature extraction
D) A change in the distribution of the input data or target variable over time

2. What is a data lake architecture designed to store primarily?

A) Highly structured data in tabular format
B) Data from a single source or department
C) Only unstructured data in raw form
D) All types of data, including structured and unstructured data

3. In a machine learning pipeline, what is the purpose of cross-validation?

A) To train multiple models on different subsets of the data to assess generalization
B) To visualize the data distribution
C) To split the dataset into training and testing sets
D) To evaluate the model's performance on new data

4. In a supervised machine learning pipeline, what is the purpose of the test data set?

A) To validate the model's performance
B) To train the machine learning model
C) To evaluate the model's predictions
D) To preprocess the data

5. In the context of data sources, what is meant by data versioning?

A) Keeping track of different versions or changes to data over time
B) Compressing data to reduce storage space
C) Storing multiple copies of the same data to increase redundancy
D) Encrypting data to protect against unauthorized access

Solutions: