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SASInstitute A00-406 Exam Syllabus Topics:

SASInstitute SAS® Viya® Supervised Machine Learning Pipelines Sample Questions:

1. In reinforcement learning, what is the "reward signal"?

A) The final prediction made by the model
B) The accuracy of the model's predictions
C) A numerical value that indicates the performance of an action taken by the agent
D) A regularization parameter

2. When deploying a model, what is "model explainability"?

A) The capability to interpret and understand the model's decisions and predictions
B) The time it takes to make predictions
C) The process of data preprocessing
D) The simplicity of the model

3. Which technique is commonly used for feature scaling or normalization in machine learning pipelines?

A) One-Hot Encoding
B) Principal Component Analysis (PCA)
C) Standardization
D) Decision Trees

4. When deploying a machine learning model, what is "model drift"?

A) A measure of feature importance
B) The process of feature extraction
C) A sudden increase in the model's accuracy
D) A change in the distribution of the input data or target variable over time

5. What is "model deployment" in the context of data science and machine learning?

A) Making the model available for use in real-world applications
B) The process of building a model
C) The process of data cleaning
D) The process of selecting features

Solutions: