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

1. 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

2. In a supervised machine learning pipeline, what is the purpose of the test data set?

A) To evaluate the model's predictions
B) To validate the model's performance
C) To train the machine learning model
D) To preprocess the data

3. What is the main purpose of feature engineering in model building?

A) Model evaluation
B) Data preprocessing
C) Data visualization
D) Creating new features or transforming existing ones to improve model performance

4. What is the primary goal of hyperparameter tuning during model building?

A) To add more features to the model
B) To improve data preprocessing techniques
C) To optimize the settings that control the model's learning process
D) To increase model complexity

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

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

Solutions: