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SASInstitute A00-406 Exam Syllabus Topics:

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

1. What does the term "bias" in machine learning refer to?

A) A model's inability to generalize to new data
B) Systematic errors that cause a model to consistently underpredict or overpredict
C) The simplicity of a model
D) The overall accuracy of a model

2. 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 selecting features
C) The process of building a model
D) The process of data cleaning

3. Which machine learning technique is typically used for building a model to predict a numeric target variable?

A) Classification
B) Regression
C) Clustering
D) Dimensionality reduction

4. In natural language processing (NLP), what is a common preprocessing step for text data before building models?

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

5. What is the purpose of regularization techniques in model building, such as L1 and L2 regularization?

A) To increase model complexity
B) To speed up model training
C) To prevent overfitting and reduce model complexity
D) To add more features to the model

Solutions: