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SASInstitute A00-406 Exam Syllabus Topics:

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

1. Which technique is used for feature selection in a machine learning pipeline when dealing with a large number of features?

A) Regularization
B) One-Hot Encoding
C) Principal Component Analysis (PCA)
D) Naive Bayes

2. What is the primary goal of building models in data science and machine learning?

A) Feature engineering
B) Data visualization
C) Data cleaning
D) Making predictions or inferences from data

3. What is the primary purpose of model deployment in the context of data science and machine learning?

A) Model evaluation
B) Making the model available for use in real-world applications
C) Model building
D) Data preprocessing

4. What is "model versioning" in the context of model deployment?

A) The process of creating synthetic data
B) The process of training a model from scratch
C) The process of evaluating model performance
D) The practice of keeping track of different versions of a model to maintain reproducibility

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

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

Solutions: