Databricks Machine Learning Associate Question 57
Select 3You are a data scientist using Databricks AutoML to build a machine learning model for predicting customer churn. After running AutoML, you notice that several models were trained, and one was selected as the best model. Which of the following steps are automatically performed by Databricks AutoML as part of the process?
- A
Splitting the dataset into training, validation, and test sets
- B
Performing hyperparameter tuning for selected algorithms
- C
Automatically deploying the best model to a production endpoint
- D
Generating a notebook to review the feature engineering and model training steps
- E
Providing an automated explanation of model predictions using SHAP values
Show answer and explanation
Correct answers: A, B, D
Explanation
Databricks AutoML automates key steps in the machine learning workflow, including dataset splitting, hyperparameter tuning, and generating a notebook for detailed insights into the modeling process. However, it does not handle deployment or provide automated SHAP-based explanations by default, which require additional configuration or manual steps.
- A. Correct.
Correct: Databricks AutoML automatically splits the dataset into training, validation, and test sets to ensure proper model evaluation.
- B. Correct.
Correct: Databricks AutoML performs hyperparameter tuning for various algorithms to optimize model performance.
- C. Incorrect.
Incorrect: AutoML does not automatically deploy the model to production. Deployment requires manual steps after model selection.
- D. Correct.
Correct: AutoML generates a detailed notebook that includes the feature engineering and model training steps for transparency and reproducibility.
- E. Incorrect.
Incorrect: While SHAP values can be used for model interpretability, Databricks AutoML does not automatically provide SHAP explanations as part of the process.