SASInstitute SAS® Viya® Supervised Machine Learning Pipelines : A00-406

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SASInstitute A00-406 Exam Syllabus Topics:

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

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

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

2. What is the primary goal of hyperparameter tuning during model building?

A) To improve data preprocessing techniques
B) To optimize the settings that control the model's learning process
C) To add more features to the model
D) To increase model complexity

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

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

4. What is the main purpose of feature engineering in model building?

A) Model evaluation
B) Data visualization
C) Creating new features or transforming existing ones to improve model performance
D) Data preprocessing

5. What does "feature selection" refer to in the context of model building?

A) The visualization of data distribution
B) The creation of synthetic features from existing data
C) The evaluation of model accuracy
D) The process of choosing the most relevant variables (features) for the model

Solutions: