Databricks Machine Learning Associate exam dumps

Databricks Machine Learning Associate practice question 87 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 87

Select 3

You are tasked with training a machine learning model in Databricks to predict customer churn. The required features are already stored in a feature store table named customer_churn_features. Which of the following steps is necessary to correctly retrieve the features for training your model using the Databricks Feature Store?

  1. A

    Use the FeatureStoreClient to read the feature store table and join it with the labels dataset.

  2. B

    Directly query the customer_churn_features table using a SQL query.

  3. C

    Create a training dataset using the FeatureStoreClient.create_training_set method.

  4. D

    Ensure that the feature store table is registered in the Databricks Feature Store workspace.

  5. E

    Train the model using the feature store table without any additional steps.

Show answer and explanation

Correct answers: A, C, D

Explanation

To train a machine learning model with features from a feature store, it is essential to use the FeatureStoreClient to read and manipulate the feature store table. This ensures that lineage, tracking, and proper feature usage are maintained. Additionally, the create_training_set method is used to join features with labels to create a valid training dataset. The feature store table must also be registered in the Databricks Feature Store workspace to enable programmatic access. Direct querying or skipping these steps can lead to a loss of functionality or incorrect model training.

  • A. Correct.

    Correct. The FeatureStoreClient is necessary for reading the feature store table and performing operations such as joining the features with the labels dataset for supervised learning.

  • B. Incorrect.

    Incorrect. While you can query the feature store table directly using SQL, this approach doesn't maintain the lineage and tracking capabilities provided by the Feature Store.

  • C. Correct.

    Correct. The create_training_set method is used to create a training dataset, ensuring that features and labels are properly joined and prepared for model training.

  • D. Correct.

    Correct. The feature store table must be registered in the Databricks Feature Store workspace for it to be accessed programmatically via the FeatureStoreClient.

  • E. Incorrect.

    Incorrect. Training a model directly using the feature store table without preparing a proper training dataset (e.g., using create_training_set) will result in an incomplete or invalid training process.

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