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SASInstitute A00-406 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Machine Learning Pipelines in SAS Viya | - Pipeline construction
|
| Topic 2: Model Evaluation and Deployment | - Model assessment metrics
|
| Topic 3: Supervised Machine Learning Models | - Regression and classification models
|
| Topic 4: Data Preparation for Machine Learning | - Data cleaning and preprocessing
|
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SASInstitute SAS® Viya® Supervised Machine Learning Pipelines Sample Questions:
What is "model versioning" in the context of model deployment?
- A. The process of training a model from scratch
- B. The process of creating synthetic data
- C. The practice of keeping track of different versions of a model to maintain reproducibility
- D. The process of evaluating model performance
Correct Answer: C 🗳️
Which algorithm is commonly used for binary classification in machine learning pipelines, especially when dealing with imbalanced datasets?
- A. Support Vector Machine (SVM)
- B. Principal Component Analysis (PCA)
- C. K-Means Clustering
- D. Linear Regression
Correct Answer: A 🗳️
In the context of data sources, what is meant by data versioning?
- A. Storing multiple copies of the same data to increase redundancy
- B. Keeping track of different versions or changes to data over time
- C. Compressing data to reduce storage space
- D. Encrypting data to protect against unauthorized access
Correct Answer: B 🗳️
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
Correct Answer: B 🗳️
When building a recommendation system, which type of filtering is based on the user's behavior and preferences?
- A. Singular Value Decomposition (SVD)
- B. Collaborative filtering
- C. Matrix factorization
- D. Content-based filtering
Correct Answer: B 🗳️
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