Exam Name: SAS® Viya® Supervised Machine Learning Pipelines
Certification Provider: SASInstitute
Corresponding Certification: SAS Certified Specialist
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SASInstitute A00-406 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Machine Learning Pipelines in SAS Viya | - Model tuning and optimization
|
| Topic 2: Supervised Machine Learning Models | - Model selection techniques
|
| Topic 3: Data Preparation for Machine Learning | - Data cleaning and preprocessing
|
| Topic 4: Model Evaluation and Deployment | - Model deployment
|
SASInstitute SAS® Viya® Supervised Machine Learning Pipelines Sample Questions:
Which feature extraction method can take both interval variables and class variables as inputs?
- A. Autoencoder
- B. Singular value decomposition
- C. Principal component analysis
- D. Robust PCA
Correct Answer: A 🗳️
In the context of data sources, what is ETL?
- A. Execute, Terminate, Launch
- B. Examine, Test, Log
- C. Efficient Text Link
- D. Extract, Transform, Load
Correct Answer: D 🗳️
What is the primary purpose of "continuous integration and continuous deployment" (CI/CD) in the context of model deployment?
- A. To visualize data distribution
- B. To create synthetic data
- C. To evaluate the model's accuracy
- D. To automate the testing, integration, and deployment of new model versions
Correct Answer: D 🗳️
What is the primary goal of A/B testing in the context of model deployment?
- A. To compare two different versions of a model or strategy to determine which performs better
- B. To assess data quality
- C. To create synthetic data
- D. To evaluate the model's accuracy
Correct Answer: A 🗳️
What is the main purpose of feature engineering in model building?
- A. Model evaluation
- B. Data visualization
- C. Data preprocessing
- D. Creating new features or transforming existing ones to improve model performance
Correct Answer: D 🗳️
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