SASInstitute SAS® Viya® Supervised Machine Learning Pipelines : A00-406 Exam Questions

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SASInstitute A00-406 Exam Syllabus Topics:

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

1. Which data source typically provides access to real-time financial market data?

A) Online news websites
B) Social media platforms
C) Stock market APIs
D) Weather stations

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. When building a deep learning neural network, what is the purpose of the activation function in each neuron?

A) To initialize the model
B) To define the learning rate
C) To control the number of hidden layers
D) To introduce non-linearity

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

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

5. What is overfitting in machine learning, and how can it be addressed in a pipeline?

A) Overfitting is not a concern in machine learning pipelines.
B) Overfitting occurs when the model is too simple and underperforms.
C) Overfitting occurs when the model is too complex and overperforms.
D) Overfitting occurs when the model fits the training data too closely and may not generalize well. It can be addressed by regularization techniques.

Solutions: