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SASInstitute A00-406 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Supervised Machine Learning Models | - Model selection techniques
|
| Topic 2: Model Evaluation and Deployment | - Model deployment
|
| Topic 3: Machine Learning Pipelines in SAS Viya | - Pipeline construction
|
| Topic 4: Data Preparation for Machine Learning | - Feature engineering
|
SASInstitute SAS® Viya® Supervised Machine Learning Pipelines Sample Questions:
1. What is the difference between a classification problem and a regression problem in machine learning?
A) Classification predicts categorical outcomes, while regression predicts numeric outcomes.
B) There is no difference; the terms are used interchangeably.
C) Regression predicts categorical outcomes, while classification predicts numeric outcomes.
D) Classification is a type of regression problem.
2. What is the primary goal of A/B testing in the context of model deployment?
A) To create synthetic data
B) To assess data quality
C) To compare two different versions of a model or strategy to determine which performs better
D) To evaluate the model's accuracy
3. Which technique is commonly used for feature scaling or normalization in machine learning pipelines?
A) One-Hot Encoding
B) Decision Trees
C) Standardization
D) Principal Component Analysis (PCA)
4. In model assessment, what does "cross-validation" aim to address?
A) Model deployment
B) Data preprocessing
C) Overfitting and generalization
D) Training a model
5. Which type of data source typically stores structured data in a tabular format?
A) APIs
B) Text documents
C) NoSQL databases
D) Relational databases
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: C | Question # 3 Answer: C | Question # 4 Answer: C | Question # 5 Answer: D |
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