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

1. When deploying a machine learning model, what is meant by "model latency"?

A) The time it takes to create synthetic data
B) The time it takes for the model to make predictions once deployed
C) The time it takes to build a model
D) The time it takes to train a model

2. What is feature engineering in the context of machine learning pipelines?

A) Applying the model to new data
B) Creating new features from existing data
C) Testing the model's performance
D) Building a machine learning model from scratch

3. When deploying a model, what is "model explainability"?

A) The process of data preprocessing
B) The capability to interpret and understand the model's decisions and predictions
C) The time it takes to make predictions
D) The simplicity of the model

4. What is the primary role of a data warehouse in an organization?

A) Long-term data storage and analysis
B) Data transformation and cleaning
C) Real-time data analysis
D) Data exploration and visualization

5. When building a recommendation system, what does "collaborative filtering" rely on?

A) Item-based clustering
B) The past behavior or preferences of users
C) The characteristics of the items being recommended
D) The popularity of items

Solutions: