Databricks Machine Learning Associate Question 49
Select 4A data scientist is using Databricks AutoML to create a machine learning model for predicting customer churn. Which steps in the machine learning workflow are automatically completed by AutoML?
- A
Data preprocessing, including handling missing values and encoding categorical features
- B
Hyperparameter tuning for selected machine learning models
- C
Manual feature engineering based on domain knowledge
- D
Training multiple machine learning models and evaluating them using metrics
- E
Deploying the best model to production
- F
Providing a detailed notebook with code for reproducibility and further customization
Show answer and explanation
Correct answers: A, B, D, F
Explanation
Databricks AutoML automates key steps in the machine learning workflow, such as data preprocessing, model selection, hyperparameter tuning, and providing a reproducible notebook. However, certain tasks like manual feature engineering and deployment remain outside its scope and require user intervention. This ensures a balance between automation and flexibility for data scientists.
- A. Correct.
Correct: Databricks AutoML automates data preprocessing tasks such as handling missing values and encoding categorical features to prepare the dataset for modeling.
- B. Correct.
Correct: Databricks AutoML includes hyperparameter tuning to optimize the performance of selected machine learning models.
- C. Incorrect.
Incorrect: Manual feature engineering based on domain knowledge is not automated by AutoML. It requires human intervention and expertise.
- D. Correct.
Correct: AutoML trains multiple machine learning models and evaluates them using metrics to identify the best-performing model.
- E. Incorrect.
Incorrect: Deploying the model to production is not completed by AutoML directly. Deployment is a separate step that must be handled manually or through integration with other tools.
- F. Correct.
Correct: Databricks AutoML generates a detailed notebook with code, enabling users to understand, reproduce, and customize the workflow further.