Databricks Machine Learning Associate exam dumps

Databricks Machine Learning Associate practice question 420 of 656

Databricks Certified Machine Learning Associate. Associate level, Databricks. Free question with the correct answer and a full explanation.

Databricks Machine Learning Associate Question 420

Select 3

A data science team is tasked with building a machine learning model to predict customer churn for a subscription service. The team decides to use Databricks AutoML for this task. Which of the following are key advantages that AutoML provides in this scenario?

  1. A

    AutoML automatically identifies the best features for the model, eliminating the need for feature engineering.

  2. B

    AutoML generates baseline models and provides comparisons between different algorithms.

  3. C

    AutoML automates hyperparameter tuning to optimize model performance.

  4. D

    AutoML ensures the final model is production-ready without requiring any further intervention.

  5. E

    AutoML provides detailed notebooks with code, enabling the team to reproduce and customize the workflow.

Show answer and explanation

Correct answers: B, C, E

Explanation

Databricks AutoML simplifies the model development process by generating baseline models, automating hyperparameter tuning, and providing reproducible notebooks with code. These features save time and improve efficiency, but some tasks like feature engineering and production-readiness still require human intervention. By leveraging these advantages, the team can focus on analyzing results and refining the model.

  • A. Incorrect.

    AutoML assists with feature selection but does not fully eliminate the need for feature engineering, as domain-specific insights may still be required.

  • B. Correct.

    AutoML generates baseline models using multiple algorithms and provides comparisons, making it easier for the team to select the most suitable approach.

  • C. Correct.

    One of the core advantages of AutoML is automating hyperparameter tuning, which helps achieve better model performance with reduced manual effort.

  • D. Incorrect.

    While AutoML facilitates model development, additional steps such as deployment, monitoring, and fine-tuning may still be required to make the model production-ready.

  • E. Correct.

    AutoML provides detailed notebooks with the generated code, which allows the team to review, reproduce, and customize the workflow as needed.

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