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SASInstitute A00-406 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Model Assessment and Deployment | 24-30% | - Deploying models into production - Assessing model performance (metrics, ROC curves, confusion matrices) |
| Building Models | 40-46% | - Model comparison and selection - Supervised model creation (decision trees, ensembles, SVM, neural networks) |
| Data Sources | 30-36% | - Importing and preparing data - Dimensionality reduction and feature engineering - Exploring and modifying data |
SASInstitute SAS® Viya® Supervised Machine Learning Pipelines Sample Questions:
Question 1
Which of the following is an example of a NoSQL database that is commonly used to store unstructured data?
A. Microsoft SQL Server
B. MySQL
C. Oracle Database
D. MongoDB
Question 2
In a supervised learning pipeline, what is the role of the training data set?
A. To test the model's generalization capability
B. To evaluate the model's predictions
C. To validate the model's performance
D. To train the machine learning model
Question 3
What is "model reevaluation" in the model deployment phase?
A. The process of selecting features
B. The periodic assessment of a deployed model's performance and potential retraining
C. The evaluation of data distribution
D. The process of data preprocessing
Question 4
What is a common example of an external data source for an organization?
A. Customer surveys
B. Employee databases
C. Intranet portals
D. Internal emails
Question 5
Which data source allows for real-time data streaming and processing?
A. Data warehouses
B. Cloud storage
C. IoT devices
D. Static data files
Solutions:
| Question 1 Answer: D | Question 2 Answer: D | Question 3 Answer: B | Question 4 Answer: A | Question 5 Answer: C |
