Databricks Machine Learning Associate exam dumps

Databricks Machine Learning Associate practice question 375 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 375

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You are working on a machine learning project where customer data is grouped by regions, and you want to train region-specific models to predict customer churn. To achieve this, you decide to use the Pandas Function API in Databricks to apply a custom training function to each group of data. Which of the following steps is required for this workflow to succeed?

  1. A

    Ensure the input DataFrame is grouped by the 'region' column before applying the function.

  2. B

    Define a custom Python function that trains a model for each group and returns the trained model for that group.

  3. C

    Use the applyInPandas method to apply the custom function to each group.

  4. D

    Ensure that the custom function takes a Pandas DataFrame as input and returns a Pandas DataFrame as output.

  5. E

    Split the input DataFrame into separate DataFrames for each region manually before applying any function.

Show answer and explanation

Correct answers: A, B, C, D

Explanation

To train region-specific models using the Pandas Function API in Databricks, the workflow involves grouping the input DataFrame by the desired column (e.g., 'region'), defining a custom training function that adheres to the Pandas Function API requirements, and applying the function to each group using the applyInPandas method. There is no need for manual data splitting since the API automatically handles applying the function to each group. This approach ensures an efficient and scalable way to train group-specific models.

  • A. Correct.

    Correct: Grouping the DataFrame by the 'region' column is essential to ensure the function is applied to each region-specific group.

  • B. Correct.

    Correct: A custom Python function is needed to train a model for each group, and this function must return the trained model or relevant outputs for that group.

  • C. Correct.

    Correct: The applyInPandas method is used to apply the custom function to each group in the grouped DataFrame.

  • D. Correct.

    Correct: The custom function must adhere to the Pandas Function API requirements, which expect the function to take a Pandas DataFrame as input and return a Pandas DataFrame as output.

  • E. Incorrect.

    Incorrect: Manually splitting the DataFrame is unnecessary because the grouping and application of the function are handled by the Pandas Function API.

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