Task 2.2: Train and Refine Models MLA-C01 Practice Questions (Page 9)

Questions 41–43

1. 41foundation · easy

   What is the primary purpose of fine-tuning a pre-trained model?

   • ATo convert the model to a different framework.
   • BTo reduce the model size by pruning weights.
   • CTo evaluate the model on a benchmark dataset.
   • DTo adapt the model to a specific task or domain using a custom dataset.
   Reveal Solution Discussion Select an answer first
2. 42application · medium

   A team is building a model to predict house prices. The dataset has 50 features, including some highly correlated features and a few with missing values. The initial model has high variance on the validation set. The team wants to improve performance and reduce overfitting. Which combination of actions should they take?

   • APerform feature selection to remove correlated features and apply L1 regularization to the model.
   • BRemove all features with missing values and train the model on the remaining features only.
   • CIncrease the model's capacity by using a deeper neural network.
   • DAdd more features by creating polynomial combinations of existing features.
   Reveal Solution Discussion Select an answer first
3. 43foundation · easy

   What is the primary purpose of SageMaker Model Registry?

   • ATo store training datasets.
   • BTo monitor deployed endpoints for drift.
   • CTo manage and version machine learning models for repeatability and auditability.
   • DTo run hyperparameter tuning jobs.
   Reveal Solution Discussion Select an answer first