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SASInstitute A00-406 Exam Syllabus Topics:

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 change in the distribution of the input data or target variable over time
C) The process of feature extraction
D) A measure of feature importance

2. Which type of model is commonly used for anomaly detection in datasets?

A) Linear Regression
B) Principal Component Analysis (PCA)
C) Decision Trees
D) Clustering Models

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

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

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

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

5. What is the primary purpose of "continuous integration and continuous deployment" (CI/CD) in the context of model deployment?

A) To evaluate the model's accuracy
B) To create synthetic data
C) To automate the testing, integration, and deployment of new model versions
D) To visualize data distribution

Solutions: